The delayed S-shaped software reliability growth model (SRGM) is one of the non-homogeneous Poisson process (NHPP) models which have been proposed for software reliability assessment. The model is distinctive because ...The delayed S-shaped software reliability growth model (SRGM) is one of the non-homogeneous Poisson process (NHPP) models which have been proposed for software reliability assessment. The model is distinctive because it has a mean value function that reflects the delay in failure reporting: there is a delay between failure detection and reporting time. The model captures error detection, isolation, and removal processes, thus is appropriate for software reliability analysis. Predictive analysis in software testing is useful in modifying, debugging, and determining when to terminate software development testing processes. However, Bayesian predictive analyses on the delayed S-shaped model have not been extensively explored. This paper uses the delayed S-shaped SRGM to address four issues in one-sample prediction associated with the software development testing process. Bayesian approach based on non-informative priors was used to derive explicit solutions for the four issues, and the developed methodologies were illustrated using real data.展开更多
In situ NMR measurements of the diffusion coefficients,including an estimate of signal strength,of lithium ion conductor using diffusion-weighting pulse sequence are performed in this study.A cascade bilinear model is...In situ NMR measurements of the diffusion coefficients,including an estimate of signal strength,of lithium ion conductor using diffusion-weighting pulse sequence are performed in this study.A cascade bilinear model is proposed to estimate the diffusion sensitivity factors of pulsed-field gradient using prior information of the electrochemical performance and Arrhenius constraint.The model postulates that the active lithium nuclei participating electrochemical reaction are relevant to the NMR signal intensity,when discharge rate or temperature condition is varying.The electrochemical data and the NMR signal strength show a highly fit with the proposed model according our simulation and experiments.Furthermore,the diffusion time is constrained by temperature based on Arrhenius equation of reaction rates dependence.An experimental calculation of Li_4Ti_5O_（12）（LTO）/carbon nanotubes（CNTs） with the electrolyte evaluating at 20 ℃ is presented,which the b factor is estimated by the discharge rate.展开更多
The original intention of visual question answering(VQA)models is to infer the answer based on the relevant information of the question text in the visual image,but many VQA models often yield answers that are biased ...The original intention of visual question answering(VQA)models is to infer the answer based on the relevant information of the question text in the visual image,but many VQA models often yield answers that are biased by some prior knowledge,especially the language priors.This paper proposes a mitigation model called language priors mitigation-VQA(LPM-VQA)for the language priors problem in VQA model,which divides language priors into positive and negative language priors.Different network branches are used to capture and process the different priors to achieve the purpose of mitigating language priors.A dynamically-changing language prior feedback objective function is designed with the intermediate results of some modules in the VQA model.The weight of the loss value for each answer is dynamically set according to the strength of its language priors to balance its proportion in the total VQA loss to further mitigate the language priors.This model does not depend on the baseline VQA architectures and can be configured like a plug-in to improve the performance of the model over most existing VQA models.The experimental results show that the proposed model is general and effective,achieving state-of-the-art accuracy in the VQA-CP v2 dataset.展开更多
Ordering based search methods have advantages over graph based search methods for structure learning of Bayesian networks in terms on the efficiency. With the aim of further increasing the accuracy of ordering based s...Ordering based search methods have advantages over graph based search methods for structure learning of Bayesian networks in terms on the efficiency. With the aim of further increasing the accuracy of ordering based search methods, we first propose to increase the search space, which can facilitate escaping from the local optima. We present our search operators with majorizations, which are easy to implement. Experiments show that the proposed algorithm can obtain significantly more accurate results. With regard to the problem of the decrease on efficiency due to the increase of the search space, we then propose to add path priors as constraints into the swap process. We analyze the coefficient which may influence the performance of the proposed algorithm, the experiments show that the constraints can enhance the efficiency greatly, while has little effect on the accuracy. The final experiments show that, compared to other competitive methods, the proposed algorithm can find better solutions while holding high efficiency at the same time on both synthetic and real data sets.展开更多
AIM To develop a framework to incorporate background domain knowledge into classification rule learning for knowledge discovery in biomedicine.METHODS Bayesian rule learning(BRL) is a rule-based classifier that uses a...AIM To develop a framework to incorporate background domain knowledge into classification rule learning for knowledge discovery in biomedicine.METHODS Bayesian rule learning(BRL) is a rule-based classifier that uses a greedy best-first search over a space of Bayesian belief-networks(BN) to find the optimal BN to explain the input dataset, and then infers classification rules from this BN. BRL uses a Bayesian score to evaluate the quality of BNs. In this paper, we extended the Bayesian score to include informative structure priors, which encodes our prior domain knowledge about the dataset. We call this extension of BRL as BRL_p. The structure prior has a λ hyperparameter that allows the user to tune the degree of incorporation of the prior knowledge in the model learning process. We studied the effect of λ on model learning using a simulated dataset and a real-world lung cancer prognostic biomarker dataset, by measuring the degree of incorporation of our specified prior knowledge. We also monitored its effect on the model predictive performance. Finally, we compared BRL_p to other stateof-the-art classifiers commonly used in biomedicine.RESULTS We evaluated the degree of incorporation of prior knowledge into BRL_p, with simulated data by measuring the Graph Edit Distance between the true datagenerating model and the model learned by BRL_p. We specified the true model using informative structurepriors. We observed that by increasing the value of λ we were able to increase the influence of the specified structure priors on model learning. A large value of λ of BRL_p caused it to return the true model. This also led to a gain in predictive performance measured by area under the receiver operator characteristic curve(AUC). We then obtained a publicly available real-world lung cancer prognostic biomarker dataset and specified a known biomarker from literature [the epidermal growth factor receptor(EGFR) gene]. We again observed that larger values of λ led to an increased incorporation of EGFR into the final BRL_p model. This relevant background knowledge also led to a gain in AUC.CONCLUSION BRL_p enables tunable structure priors to be incorporated during Bayesian classification rule learning that integrates data and knowledge as demonstrated using lung cancer biomarker data.展开更多
Testability plays an important role in improving the readiness and decreasing the lifecycle cost of equipment. Testability demonstration and evaluation is of significance in measuring such testability indexes as fault...Testability plays an important role in improving the readiness and decreasing the lifecycle cost of equipment. Testability demonstration and evaluation is of significance in measuring such testability indexes as fault detection rate（FDR） and fault isolation rate（FIR）, which is useful to the producer in mastering the testability level and improving the testability design, and helpful to the consumer in making purchase decisions. Aiming at the problems with a small sample of testability demonstration test data（TDTD） such as low evaluation confidence and inaccurate result, a testability evaluation method is proposed based on the prior information of multiple sources and Bayes theory. Firstly, the types of prior information are analyzed. The maximum entropy method is applied to the prior information with the mean and interval estimate forms on the testability index to obtain the parameters of prior probability density function（PDF）, and the empirical Bayesian method is used to get the parameters for the prior information with a success-fail form. Then, a parametrical data consistency check method is used to check the compatibility between all the sources of prior information and TDTD. For the prior information to pass the check, the prior credibility is calculated. A mixed prior distribution is formed based on the prior PDFs and the corresponding credibility. The Bayesian posterior distribution model is acquired with the mixed prior distribution and TDTD, based on which the point and interval estimates are calculated.Finally, examples of a flying control system are used to verify the proposed method. The results show that the proposed method is feasible and effective.展开更多
In this work, the effect of prior cold deformation on the stability of retained austenite in GCr15 bearing steel was investigated after quenching and tempering treatment. The thermal stability was evaluated by calcula...In this work, the effect of prior cold deformation on the stability of retained austenite in GCr15 bearing steel was investigated after quenching and tempering treatment. The thermal stability was evaluated by calculating thermal activation energy for decomposition of retained austenite using differential scanning calorimeter. The mechanical stability was investigated according to the strain-induced martensitic transformation behavior of retained austenite under the standard compression testing. It is found that the prior cold deformation not only accelerates the carbide dissolution during the austenitization process but also contributes to the carbon partitioning in the tempering stage due to the higher density of phase boundaries, which results in the improvement of the thermal stability of retained austenite. Due to the enhanced carbide dissolution, the higher carbon content in the prior austenite will intensify the isotropic strain of martensitic transformation. As a consequence, the film-like retained austenite is likely to form under a higher hydrostatic pressure and thus shows a higher mechanical stability. Additionally, it is noteworthy that the benefits of the prior cold deformation to the stability of retained austenite would be saturated when the cold deformation degree is larger than 40%.展开更多
Based on the concept of admissibility in statistics, a definition of generalized admissibility of Bayes estimates has been given at first, which was with inaccurate prior for the application in surveying adjustment. T...Based on the concept of admissibility in statistics, a definition of generalized admissibility of Bayes estimates has been given at first, which was with inaccurate prior for the application in surveying adjustment. Then according to the definition, the generalized admissibility of the normal linear Bayes estimate with the inaccurate prior information that contains deviations or model errors, as well as how to eliminate the effect of the model error on the Bayes estimate in surveying adjustment were studied. The results show that if the prior information is not accurate, that is, it contains model error, the generalized admissibility can explain whether the Bayes estimate can be accepted or not. For the case of linear normal Bayes estimate, the Bayes estimate can be made generally admissible by giving a less prior weight if the prior information is inaccurate. Finally an example was given.展开更多
The effect of prior corrosion on the mechanical properties of 7475-T761 aluminum alloy was investigated by immersion test, stress corrosion test, cathode charge method and electrochemical polarization test. Results sh...The effect of prior corrosion on the mechanical properties of 7475-T761 aluminum alloy was investigated by immersion test, stress corrosion test, cathode charge method and electrochemical polarization test. Results show that prior corrosion in the solution with 3 wt% NaC1 and 0.5 wt% H202 leads to mechanical properties deterioration of 7475-T761 aluminum alloy. Moreover, the elongation decreases significantly. This is mainly attributed to electrochemical corrosion and hydrogen embrittlement, in which corrosion plays a major role. Tensile stress promotes the degradation of the mechanical properties by accelerating the pitting corrosion and hydrogen embrittlement.展开更多
Smoothness prior approach for spectral smoothing is investigated using Fourier frequency filter analysis.We show that the regularization parameter in penalized least squares could continuously control the bandwidth of...Smoothness prior approach for spectral smoothing is investigated using Fourier frequency filter analysis.We show that the regularization parameter in penalized least squares could continuously control the bandwidth of low-pass filter.Besides,due to its property of interpolating the missing values automatically and smoothly,a spectral baseline correction algorithm based on the approach is proposed.This algorithm generally comprises spectral peak detection and baseline estimation.First,the spectral peak regions are detected and identified according to the second derivatives.Then,generalized smoothness prior approach combining identification information could estimate the baseline in peak regions.Results with both the simulated and real spectra show accurate baseline-corrected signals with this method.展开更多
3D object detection is one of the most challenging research tasks in computer vision. In order to solve the problem of template information dependency of 3D object proposal in the method of 3D object detection based o...3D object detection is one of the most challenging research tasks in computer vision. In order to solve the problem of template information dependency of 3D object proposal in the method of 3D object detection based on 2.5D information, we proposed a 3D object detector based on fusion of vanishing point and prior orientation, which estimates an accurate 3D proposal from 2.5D data, and provides an excellent start point for 3D object classification and localization. The algorithm first calculates three mutually orthogonal vanishing points by the Euler angle principle and projects them into the pixel coordinate system. Then, the top edge of the 2D proposal is sampled by the preset sampling pitch, and the first one vertex is taken. Finally, the remaining seven vertices of the 3D proposal are calculated according to the linear relationship between the three vanishing points and the vertices, and the complete information of the 3D proposal is obtained. The experimental results show that this proposed method improves the Mean Average Precision score by 2.7% based on the Amodal3Det method.展开更多
Isothermal transformation （TTT） behavior of the low carbon steels with two Si contents （0.50 wt pct and 1.35 wt pct） was investigated with and without the prior deformation. The results show that Si and the prior ...Isothermal transformation （TTT） behavior of the low carbon steels with two Si contents （0.50 wt pct and 1.35 wt pct） was investigated with and without the prior deformation. The results show that Si and the prior deformation of the austenite have significant effects on the transformation of the ferrite and bainite. The addition of Si refines the ferrite grains, accelerates the polygonal ferrite transformation and the formation of M/A constituents, leading to the improvement of the strength. The ferrite grains formed under the prior deformation of the austenite become more homogeneous and refined. However, the influence of deformation on the tensile strength of both steels is dependent on the isothermal temperatures. Thermodynamic calculation indicates that Si and prior deformation reduce the incubation time of both ferrite and bainite transformation, but the effect is weakened by the decrease of the isothermal temperatures.展开更多
Focusing on the degradation of foggy images, a restora- tion approach from a single image based on spatial correlation of dark channel prior is proposed. Firstly, the transmission of each pixel is estimated by the spa...Focusing on the degradation of foggy images, a restora- tion approach from a single image based on spatial correlation of dark channel prior is proposed. Firstly, the transmission of each pixel is estimated by the spatial correlation of dark channel prior. Secondly, a degradation model is utilized to restore the foggy image. Thirdly, the final recovered image, with enhanced contrast, is obtained by performing a post-processing technique based on just-noticeable difference. Experimental results demonstrate that the information of a foggy image can be recovered perfectly by the proposed method, even in the case of the abrupt depth changing scene.展开更多
Yin [1] has developed a new Bayesian measure of evidence for testing a point null hypothesis which agrees with the frequentist p-value thereby, solving Lindley’s paradox. Yin and Li [2] extended the methodology of Yi...Yin [1] has developed a new Bayesian measure of evidence for testing a point null hypothesis which agrees with the frequentist p-value thereby, solving Lindley’s paradox. Yin and Li [2] extended the methodology of Yin [1] to the case of the Behrens-Fisher problem by assigning Jeffreys’ independent prior to the nuisance parameters. In this paper, we were able to show both analytically and through the results from simulation studies that the methodology of Yin?[1] solves simultaneously, the Behrens-Fisher problem and Lindley’s paradox when a Gamma prior is assigned to the nuisance parameters.展开更多
The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is...The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is based on the dark channel prior principle and aims at the prior information absent blurred image degradation situation. A lot of improvements have been made to estimate the transmission map of blurred images. Since the dark channel prior principle can effectively restore the blurred image at the cost of a large amount of computation, the total variation （TV） and image morphology transform （specifically top-hat transform and bottom- hat transform） have been introduced into the improved method. Compared with original transmission map estimation methods, the proposed method features both simplicity and accuracy. The es- timated transmission map together with the element can restore the image. Simulation results show that this method could inhibit the ill-posed problem during image restoration, meanwhile it can greatly improve the image quality and definition.展开更多
文摘The delayed S-shaped software reliability growth model (SRGM) is one of the non-homogeneous Poisson process (NHPP) models which have been proposed for software reliability assessment. The model is distinctive because it has a mean value function that reflects the delay in failure reporting: there is a delay between failure detection and reporting time. The model captures error detection, isolation, and removal processes, thus is appropriate for software reliability analysis. Predictive analysis in software testing is useful in modifying, debugging, and determining when to terminate software development testing processes. However, Bayesian predictive analyses on the delayed S-shaped model have not been extensively explored. This paper uses the delayed S-shaped SRGM to address four issues in one-sample prediction associated with the software development testing process. Bayesian approach based on non-informative priors was used to derive explicit solutions for the four issues, and the developed methodologies were illustrated using real data.
基金supported by the National Major Scientific Equipment R&D Project (No. ZDYZ2010-2)the National Natural Science Foundation of China (No. 51307165)
文摘In situ NMR measurements of the diffusion coefficients,including an estimate of signal strength,of lithium ion conductor using diffusion-weighting pulse sequence are performed in this study.A cascade bilinear model is proposed to estimate the diffusion sensitivity factors of pulsed-field gradient using prior information of the electrochemical performance and Arrhenius constraint.The model postulates that the active lithium nuclei participating electrochemical reaction are relevant to the NMR signal intensity,when discharge rate or temperature condition is varying.The electrochemical data and the NMR signal strength show a highly fit with the proposed model according our simulation and experiments.Furthermore,the diffusion time is constrained by temperature based on Arrhenius equation of reaction rates dependence.An experimental calculation of Li_4Ti_5O_（12）（LTO）/carbon nanotubes（CNTs） with the electrolyte evaluating at 20 ℃ is presented,which the b factor is estimated by the discharge rate.
文摘The original intention of visual question answering(VQA)models is to infer the answer based on the relevant information of the question text in the visual image,but many VQA models often yield answers that are biased by some prior knowledge,especially the language priors.This paper proposes a mitigation model called language priors mitigation-VQA(LPM-VQA)for the language priors problem in VQA model,which divides language priors into positive and negative language priors.Different network branches are used to capture and process the different priors to achieve the purpose of mitigating language priors.A dynamically-changing language prior feedback objective function is designed with the intermediate results of some modules in the VQA model.The weight of the loss value for each answer is dynamically set according to the strength of its language priors to balance its proportion in the total VQA loss to further mitigate the language priors.This model does not depend on the baseline VQA architectures and can be configured like a plug-in to improve the performance of the model over most existing VQA models.The experimental results show that the proposed model is general and effective,achieving state-of-the-art accuracy in the VQA-CP v2 dataset.
基金supported by the National Natural Science Fundation of China(61573285)the Doctoral Fundation of China(2013ZC53037)
文摘Ordering based search methods have advantages over graph based search methods for structure learning of Bayesian networks in terms on the efficiency. With the aim of further increasing the accuracy of ordering based search methods, we first propose to increase the search space, which can facilitate escaping from the local optima. We present our search operators with majorizations, which are easy to implement. Experiments show that the proposed algorithm can obtain significantly more accurate results. With regard to the problem of the decrease on efficiency due to the increase of the search space, we then propose to add path priors as constraints into the swap process. We analyze the coefficient which may influence the performance of the proposed algorithm, the experiments show that the constraints can enhance the efficiency greatly, while has little effect on the accuracy. The final experiments show that, compared to other competitive methods, the proposed algorithm can find better solutions while holding high efficiency at the same time on both synthetic and real data sets.
基金Supported by National Institute of General Medical Sciences of the National Institutes of Health,No.R01GM100387
文摘AIM To develop a framework to incorporate background domain knowledge into classification rule learning for knowledge discovery in biomedicine.METHODS Bayesian rule learning(BRL) is a rule-based classifier that uses a greedy best-first search over a space of Bayesian belief-networks(BN) to find the optimal BN to explain the input dataset, and then infers classification rules from this BN. BRL uses a Bayesian score to evaluate the quality of BNs. In this paper, we extended the Bayesian score to include informative structure priors, which encodes our prior domain knowledge about the dataset. We call this extension of BRL as BRL_p. The structure prior has a λ hyperparameter that allows the user to tune the degree of incorporation of the prior knowledge in the model learning process. We studied the effect of λ on model learning using a simulated dataset and a real-world lung cancer prognostic biomarker dataset, by measuring the degree of incorporation of our specified prior knowledge. We also monitored its effect on the model predictive performance. Finally, we compared BRL_p to other stateof-the-art classifiers commonly used in biomedicine.RESULTS We evaluated the degree of incorporation of prior knowledge into BRL_p, with simulated data by measuring the Graph Edit Distance between the true datagenerating model and the model learned by BRL_p. We specified the true model using informative structurepriors. We observed that by increasing the value of λ we were able to increase the influence of the specified structure priors on model learning. A large value of λ of BRL_p caused it to return the true model. This also led to a gain in predictive performance measured by area under the receiver operator characteristic curve(AUC). We then obtained a publicly available real-world lung cancer prognostic biomarker dataset and specified a known biomarker from literature [the epidermal growth factor receptor(EGFR) gene]. We again observed that larger values of λ led to an increased incorporation of EGFR into the final BRL_p model. This relevant background knowledge also led to a gain in AUC.CONCLUSION BRL_p enables tunable structure priors to be incorporated during Bayesian classification rule learning that integrates data and knowledge as demonstrated using lung cancer biomarker data.
基金co-supported by the National Natural Science Foundation of China(No.51105369)Shanghai Aerospace Science and Technology Foundation(No.SAST201313)
文摘Testability plays an important role in improving the readiness and decreasing the lifecycle cost of equipment. Testability demonstration and evaluation is of significance in measuring such testability indexes as fault detection rate（FDR） and fault isolation rate（FIR）, which is useful to the producer in mastering the testability level and improving the testability design, and helpful to the consumer in making purchase decisions. Aiming at the problems with a small sample of testability demonstration test data（TDTD） such as low evaluation confidence and inaccurate result, a testability evaluation method is proposed based on the prior information of multiple sources and Bayes theory. Firstly, the types of prior information are analyzed. The maximum entropy method is applied to the prior information with the mean and interval estimate forms on the testability index to obtain the parameters of prior probability density function（PDF）, and the empirical Bayesian method is used to get the parameters for the prior information with a success-fail form. Then, a parametrical data consistency check method is used to check the compatibility between all the sources of prior information and TDTD. For the prior information to pass the check, the prior credibility is calculated. A mixed prior distribution is formed based on the prior PDFs and the corresponding credibility. The Bayesian posterior distribution model is acquired with the mixed prior distribution and TDTD, based on which the point and interval estimates are calculated.Finally, examples of a flying control system are used to verify the proposed method. The results show that the proposed method is feasible and effective.
基金supported by the National Natural Science Foundation of China (Nos. 51575414 and 51605354)the 111 Project (B17034), the China Postdoctoral Science Foundation (No. 2017M612524)the State Key Laboratory of Materials Processing and Die & Mould Technology, Huazhong University of Science and Technology (P2019-017)
文摘In this work, the effect of prior cold deformation on the stability of retained austenite in GCr15 bearing steel was investigated after quenching and tempering treatment. The thermal stability was evaluated by calculating thermal activation energy for decomposition of retained austenite using differential scanning calorimeter. The mechanical stability was investigated according to the strain-induced martensitic transformation behavior of retained austenite under the standard compression testing. It is found that the prior cold deformation not only accelerates the carbide dissolution during the austenitization process but also contributes to the carbon partitioning in the tempering stage due to the higher density of phase boundaries, which results in the improvement of the thermal stability of retained austenite. Due to the enhanced carbide dissolution, the higher carbon content in the prior austenite will intensify the isotropic strain of martensitic transformation. As a consequence, the film-like retained austenite is likely to form under a higher hydrostatic pressure and thus shows a higher mechanical stability. Additionally, it is noteworthy that the benefits of the prior cold deformation to the stability of retained austenite would be saturated when the cold deformation degree is larger than 40%.
文摘Based on the concept of admissibility in statistics, a definition of generalized admissibility of Bayes estimates has been given at first, which was with inaccurate prior for the application in surveying adjustment. Then according to the definition, the generalized admissibility of the normal linear Bayes estimate with the inaccurate prior information that contains deviations or model errors, as well as how to eliminate the effect of the model error on the Bayes estimate in surveying adjustment were studied. The results show that if the prior information is not accurate, that is, it contains model error, the generalized admissibility can explain whether the Bayes estimate can be accepted or not. For the case of linear normal Bayes estimate, the Bayes estimate can be made generally admissible by giving a less prior weight if the prior information is inaccurate. Finally an example was given.
基金financially supported by the National Natural Science Foundation of China(No.51171154)the National Defense Key Disciplines Laboratory of Light Alloy Processing Science and Technology,Nanchang Hangkong University(Grant No.gf 201401001)
文摘The effect of prior corrosion on the mechanical properties of 7475-T761 aluminum alloy was investigated by immersion test, stress corrosion test, cathode charge method and electrochemical polarization test. Results show that prior corrosion in the solution with 3 wt% NaC1 and 0.5 wt% H202 leads to mechanical properties deterioration of 7475-T761 aluminum alloy. Moreover, the elongation decreases significantly. This is mainly attributed to electrochemical corrosion and hydrogen embrittlement, in which corrosion plays a major role. Tensile stress promotes the degradation of the mechanical properties by accelerating the pitting corrosion and hydrogen embrittlement.
基金Supported by the National Basic Research Program of China(61178072)
文摘Smoothness prior approach for spectral smoothing is investigated using Fourier frequency filter analysis.We show that the regularization parameter in penalized least squares could continuously control the bandwidth of low-pass filter.Besides,due to its property of interpolating the missing values automatically and smoothly,a spectral baseline correction algorithm based on the approach is proposed.This algorithm generally comprises spectral peak detection and baseline estimation.First,the spectral peak regions are detected and identified according to the second derivatives.Then,generalized smoothness prior approach combining identification information could estimate the baseline in peak regions.Results with both the simulated and real spectra show accurate baseline-corrected signals with this method.
基金Supported by the National Natural Science Foundation of China(61772328,61802253,61831018)
文摘3D object detection is one of the most challenging research tasks in computer vision. In order to solve the problem of template information dependency of 3D object proposal in the method of 3D object detection based on 2.5D information, we proposed a 3D object detector based on fusion of vanishing point and prior orientation, which estimates an accurate 3D proposal from 2.5D data, and provides an excellent start point for 3D object classification and localization. The algorithm first calculates three mutually orthogonal vanishing points by the Euler angle principle and projects them into the pixel coordinate system. Then, the top edge of the 2D proposal is sampled by the preset sampling pitch, and the first one vertex is taken. Finally, the remaining seven vertices of the 3D proposal are calculated according to the linear relationship between the three vanishing points and the vertices, and the complete information of the 3D proposal is obtained. The experimental results show that this proposed method improves the Mean Average Precision score by 2.7% based on the Amodal3Det method.
基金the Baoshan Iron and Steel Group for the financial support
文摘Isothermal transformation （TTT） behavior of the low carbon steels with two Si contents （0.50 wt pct and 1.35 wt pct） was investigated with and without the prior deformation. The results show that Si and the prior deformation of the austenite have significant effects on the transformation of the ferrite and bainite. The addition of Si refines the ferrite grains, accelerates the polygonal ferrite transformation and the formation of M/A constituents, leading to the improvement of the strength. The ferrite grains formed under the prior deformation of the austenite become more homogeneous and refined. However, the influence of deformation on the tensile strength of both steels is dependent on the isothermal temperatures. Thermodynamic calculation indicates that Si and prior deformation reduce the incubation time of both ferrite and bainite transformation, but the effect is weakened by the decrease of the isothermal temperatures.
基金supported by "the Twelfth Five-year Civil Aerospace Technologies Pre-Research Program"(D040201)
文摘Focusing on the degradation of foggy images, a restora- tion approach from a single image based on spatial correlation of dark channel prior is proposed. Firstly, the transmission of each pixel is estimated by the spatial correlation of dark channel prior. Secondly, a degradation model is utilized to restore the foggy image. Thirdly, the final recovered image, with enhanced contrast, is obtained by performing a post-processing technique based on just-noticeable difference. Experimental results demonstrate that the information of a foggy image can be recovered perfectly by the proposed method, even in the case of the abrupt depth changing scene.
文摘Yin [1] has developed a new Bayesian measure of evidence for testing a point null hypothesis which agrees with the frequentist p-value thereby, solving Lindley’s paradox. Yin and Li [2] extended the methodology of Yin [1] to the case of the Behrens-Fisher problem by assigning Jeffreys’ independent prior to the nuisance parameters. In this paper, we were able to show both analytically and through the results from simulation studies that the methodology of Yin?[1] solves simultaneously, the Behrens-Fisher problem and Lindley’s paradox when a Gamma prior is assigned to the nuisance parameters.
基金supported by the National Natural Science Foundation of China(61301095)the Chinese University Scientific Fund(HEUCF130807)the Chinese Defense Advanced Research Program of Science and Technology(10J3.1.6)
文摘The blurred image restoration method can dramatically highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap- plications. This paper is based on the dark channel prior principle and aims at the prior information absent blurred image degradation situation. A lot of improvements have been made to estimate the transmission map of blurred images. Since the dark channel prior principle can effectively restore the blurred image at the cost of a large amount of computation, the total variation （TV） and image morphology transform （specifically top-hat transform and bottom- hat transform） have been introduced into the improved method. Compared with original transmission map estimation methods, the proposed method features both simplicity and accuracy. The es- timated transmission map together with the element can restore the image. Simulation results show that this method could inhibit the ill-posed problem during image restoration, meanwhile it can greatly improve the image quality and definition.
