To emulate the functionality of the human retina and achieve a neuromorphic visual system,the development of a photonic synapse capable of multispectral color discrimination is of paramount importance.However,attainin...To emulate the functionality of the human retina and achieve a neuromorphic visual system,the development of a photonic synapse capable of multispectral color discrimination is of paramount importance.However,attaining robust color discrimination across a wide intensity range,even irrespective of medium limitations in the channel layer,poses a significant challenge.Here,we propose an approach that can bestow the color-discriminating synaptic functionality upon a three-terminal transistor flash memory even with enhanced discriminating capabilities.By incorporating the strong induced dipole moment effect at the excitation,modulated by the wavelength of the incident light,into the floating gate,we achieve outstanding RGB color-discriminating synaptic functionality within a remarkable intensity range spanning from 0.05 to 40 mW cm^(-2).This approach is not restricted to a specific medium in the channel layer,thereby enhancing its applicability.The effectiveness of this color-discriminating synaptic functionality is demonstrated through visual pre-processing of a photonic synapse array,involving the differentiation of RGB channels and the enhancement of image contrast with noise reduction.Consequently,a convolutional neural network can achieve an impressive inference accuracy of over 94%for Canadian-Institute-For-Advanced-Research-10 colorful image recognition task after the pre-processing.Our proposed approach offers a promising solution for achieving robust and versatile RGB color discrimination in photonic synapses,enabling significant advancements in artificial visual systems.展开更多
This paper was to develop a model for simulating the leaf color changes in rice （Oryza sativa L.） based on RGB （red, green, and blue） values. Based on rice experiment data with different cultivars and nitrogen （N...This paper was to develop a model for simulating the leaf color changes in rice （Oryza sativa L.） based on RGB （red, green, and blue） values. Based on rice experiment data with different cultivars and nitrogen （N） rates, the time-course RGB values of each leaf on main stem were collected during the growth period in rice, and a model for simulating the dynamics of leaf color in rice was then developed using quantitative modeling technology. The results showed that the RGB values of leaf color gradually decreased from the initial values （light green） to the steady values （green） during the first stage, remained the steady values （green） during the second stage, then gradually increased to the final values （from green to yellow） during the third stage. The decreasing linear functions, constant functions and increasing linear functions were used to simulate the changes in RGB values of leaf color at the first, second and third stages with growing degree days （GDD）, respectively; two cultivar parameters, MatRGB （leaf color matrix） and AR （a vector composed of the ratio of the cumulative GDD of each stage during color change process of leaf n to that during leaf n drawn under adequate N status）, were introduced to quantify the genetic characters in RGB values of leaf color and in durations of different stages during leaf color change, respectively; FN （N impact factor） was used to quantify the effects of N levels on RGB values of leaf color and on durations of different stages during leaf color change; linear functions were applied to simulate the changes in leaf color along the leaf midvein direction during leaf development process. Validation of the models with the independent experiment dataset exhibited that the root mean square errors （RMSE） between the observed and simulated RGB values were among 8 to 13, the relative RMSE （RRMSE） were among 8 to 10%, the mean absolute differences （da） were among 3.85 to 6.90, and the ratio of da to the mean observation values （Clap） were among 3.04 to 4.90%. In addition, the leaf color model was used to render the leaf color change over growth progress using the technology of visualization, with a good performance on predicting dynamic changes in rice leaf color. These results would provide a technical support for further developing virtual plant during rice growth and development.展开更多
Colors of textile materials are the first parameter of quality evaluated by consumers and a key component considered in selecting printed fabric. In the textiles industry, digital printed fabric analysis is one of the...Colors of textile materials are the first parameter of quality evaluated by consumers and a key component considered in selecting printed fabric. In the textiles industry, digital printed fabric analysis is one of the basic elements in successfully utilizing a color mechanism scheme and objectively evaluating fabric color alterations. Precise color measurement, however, is mostly used in sample analysis and quality inspection which help to produce reproducible or similar product. It is important that for quality inspection, the color of the product should be measured as a necessary requirement of quality control whether the product is to be accepted or not. Presented in this study is an unsupervised segmentation of printed fabrics patterns using mean shift algorithm and color measurements over the segmented regions of printed fabric patterns. The results established a consistent and reliable color measurement of multiple color patterns and appearance with the established range without any interactions.展开更多
In order to solve the uncertainty of voice-to-color conversion in which one of the three voice features（loudness, tone, rhythm） is applied to control LED color, a linear conversion solution is proposed. And a chroma...In order to solve the uncertainty of voice-to-color conversion in which one of the three voice features（loudness, tone, rhythm） is applied to control LED color, a linear conversion solution is proposed. And a chromaticity diagram is defined by using hue definition on hue-saturation-lightness（HSL） hue ring and the normalization of CIE xyY which is a color standard defined by International Commission on Illumination（CIE）. The chromaticity diagram shows a linear relation between pitch and color, which is referred to conversions of other physical parameters as well. Based on the solution, red（R）, green（G） and blue（B） LEDs, the driving structure of a conversion circuit is designed and set up. The results indicate that signal processing of tone-to-color conversion is effective, from 30 Hz to 3 kHz with a resolution of 10 Hz mapped to the chromaticity diagram.展开更多
针对RGB-D(Red Green Blue Depth)语义分割中色彩信息和深度信息无法有效融合以及无法充分提取多尺度上下文信息的问题,文中提出了一种基于双流聚合Transformer的RGB-D语义分割方法。通过Transformer提取全彩图像和深度图像的多层次特征...针对RGB-D(Red Green Blue Depth)语义分割中色彩信息和深度信息无法有效融合以及无法充分提取多尺度上下文信息的问题,文中提出了一种基于双流聚合Transformer的RGB-D语义分割方法。通过Transformer提取全彩图像和深度图像的多层次特征,采用通道注意交叉融合模块与深度增强RGB操作实现各层次特征模态鸿沟的补偿,完成双模态信息融合。使用多层聚合解码器模块整合多层次多尺度上下文特征,减少了信息传递损失,实现了更准确和更全面的语义分割。实验结果表明,所提方法在NYU-Dv2数据集上的平均交并比(mean Intersection over Union,mIoU)、像素准确率和平均像素准确率分别达到52.9%、78.0%、66.0%。在Cityscapes数据集上的实验结果表明,在低分辨率输入图像下,所提方法的mIoU达到了79.8%。展开更多
基金supported by National Research Foundation of Korea(NRF)[RS-2024-00350701 and RS-2023-00207828].
文摘To emulate the functionality of the human retina and achieve a neuromorphic visual system,the development of a photonic synapse capable of multispectral color discrimination is of paramount importance.However,attaining robust color discrimination across a wide intensity range,even irrespective of medium limitations in the channel layer,poses a significant challenge.Here,we propose an approach that can bestow the color-discriminating synaptic functionality upon a three-terminal transistor flash memory even with enhanced discriminating capabilities.By incorporating the strong induced dipole moment effect at the excitation,modulated by the wavelength of the incident light,into the floating gate,we achieve outstanding RGB color-discriminating synaptic functionality within a remarkable intensity range spanning from 0.05 to 40 mW cm^(-2).This approach is not restricted to a specific medium in the channel layer,thereby enhancing its applicability.The effectiveness of this color-discriminating synaptic functionality is demonstrated through visual pre-processing of a photonic synapse array,involving the differentiation of RGB channels and the enhancement of image contrast with noise reduction.Consequently,a convolutional neural network can achieve an impressive inference accuracy of over 94%for Canadian-Institute-For-Advanced-Research-10 colorful image recognition task after the pre-processing.Our proposed approach offers a promising solution for achieving robust and versatile RGB color discrimination in photonic synapses,enabling significant advancements in artificial visual systems.
基金the National High-Tech R&D Program of China(2013AA100404,2012AA101306-2)the Priority Academic Program Development of Jiangsu Higher Education Institutions of China(PAPD)
文摘This paper was to develop a model for simulating the leaf color changes in rice （Oryza sativa L.） based on RGB （red, green, and blue） values. Based on rice experiment data with different cultivars and nitrogen （N） rates, the time-course RGB values of each leaf on main stem were collected during the growth period in rice, and a model for simulating the dynamics of leaf color in rice was then developed using quantitative modeling technology. The results showed that the RGB values of leaf color gradually decreased from the initial values （light green） to the steady values （green） during the first stage, remained the steady values （green） during the second stage, then gradually increased to the final values （from green to yellow） during the third stage. The decreasing linear functions, constant functions and increasing linear functions were used to simulate the changes in RGB values of leaf color at the first, second and third stages with growing degree days （GDD）, respectively; two cultivar parameters, MatRGB （leaf color matrix） and AR （a vector composed of the ratio of the cumulative GDD of each stage during color change process of leaf n to that during leaf n drawn under adequate N status）, were introduced to quantify the genetic characters in RGB values of leaf color and in durations of different stages during leaf color change, respectively; FN （N impact factor） was used to quantify the effects of N levels on RGB values of leaf color and on durations of different stages during leaf color change; linear functions were applied to simulate the changes in leaf color along the leaf midvein direction during leaf development process. Validation of the models with the independent experiment dataset exhibited that the root mean square errors （RMSE） between the observed and simulated RGB values were among 8 to 13, the relative RMSE （RRMSE） were among 8 to 10%, the mean absolute differences （da） were among 3.85 to 6.90, and the ratio of da to the mean observation values （Clap） were among 3.04 to 4.90%. In addition, the leaf color model was used to render the leaf color change over growth progress using the technology of visualization, with a good performance on predicting dynamic changes in rice leaf color. These results would provide a technical support for further developing virtual plant during rice growth and development.
文摘Colors of textile materials are the first parameter of quality evaluated by consumers and a key component considered in selecting printed fabric. In the textiles industry, digital printed fabric analysis is one of the basic elements in successfully utilizing a color mechanism scheme and objectively evaluating fabric color alterations. Precise color measurement, however, is mostly used in sample analysis and quality inspection which help to produce reproducible or similar product. It is important that for quality inspection, the color of the product should be measured as a necessary requirement of quality control whether the product is to be accepted or not. Presented in this study is an unsupervised segmentation of printed fabrics patterns using mean shift algorithm and color measurements over the segmented regions of printed fabric patterns. The results established a consistent and reliable color measurement of multiple color patterns and appearance with the established range without any interactions.
文摘In order to solve the uncertainty of voice-to-color conversion in which one of the three voice features（loudness, tone, rhythm） is applied to control LED color, a linear conversion solution is proposed. And a chromaticity diagram is defined by using hue definition on hue-saturation-lightness（HSL） hue ring and the normalization of CIE xyY which is a color standard defined by International Commission on Illumination（CIE）. The chromaticity diagram shows a linear relation between pitch and color, which is referred to conversions of other physical parameters as well. Based on the solution, red（R）, green（G） and blue（B） LEDs, the driving structure of a conversion circuit is designed and set up. The results indicate that signal processing of tone-to-color conversion is effective, from 30 Hz to 3 kHz with a resolution of 10 Hz mapped to the chromaticity diagram.
文摘针对RGB-D(Red Green Blue Depth)语义分割中色彩信息和深度信息无法有效融合以及无法充分提取多尺度上下文信息的问题,文中提出了一种基于双流聚合Transformer的RGB-D语义分割方法。通过Transformer提取全彩图像和深度图像的多层次特征,采用通道注意交叉融合模块与深度增强RGB操作实现各层次特征模态鸿沟的补偿,完成双模态信息融合。使用多层聚合解码器模块整合多层次多尺度上下文特征,减少了信息传递损失,实现了更准确和更全面的语义分割。实验结果表明,所提方法在NYU-Dv2数据集上的平均交并比(mean Intersection over Union,mIoU)、像素准确率和平均像素准确率分别达到52.9%、78.0%、66.0%。在Cityscapes数据集上的实验结果表明,在低分辨率输入图像下,所提方法的mIoU达到了79.8%。
