of complete genome sequences submitted directly from sequencing projects are diverse in terms of annotation strategies and update frequencies. These inconsistencies make comparative studies difficult. To allow rapid d...of complete genome sequences submitted directly from sequencing projects are diverse in terms of annotation strategies and update frequencies. These inconsistencies make comparative studies difficult. To allow rapid data preparation of a large number of complete genomes, automation and speed are important for genome re-annotation. Here we introduce an open-source rapid genome re-annotation software system, Restauro-G, specialized for bacterial genomes. Restauro-G re-annotates a genome by similarity searches utilizing the BLASTLike Alignment Tool, referring to protein databases such as UniProt KB, NCBI nr, NCBI COGs, Pfam, and PSORTb. Re-annotation by Restauro-G achieved over 98% accuracy for most bacterial chromosomes in comparison with the original manually curated annotation of EMBL releases. Restauro-G was developed in the generic bioinformatics workbench G-language Genome Analysis Environment and is distributed at http：//restauro-g.iab.keio.ac.jp/ under the GNU General Public License.展开更多
Understanding the functional effects of genetic variants is crucial in modern genomics and genetics. Transcription factor binding sites （TFBSs） are one of the most important cis-regulatory elements. While multiple t...Understanding the functional effects of genetic variants is crucial in modern genomics and genetics. Transcription factor binding sites （TFBSs） are one of the most important cis-regulatory elements. While multiple tools have been developed to assess functional effects of genetic variants at TFBSs, they usually assume that each variant works in isolation and neglect the potential ＂interference＂ among multiple variants within the same TFBS. In this study, we presented COPE-TFBS （Context-Oriented Predictor for variant Effect on Transcription Factor Binding Site）, a novel method that considers sequence context to accurately predict variant effects on TFBSs. We systematically re-analyzed the sequencing data from both the 1000 Genomes Project and the Genotype-Tissue Expression （GTEx） Project via COPE-TFBS, and identified numbers of novel TFBSs, transformed TFBSs and discordantly annotated TFBSs resulting from multiple variants, further highlighting the necessity of sequence context in accurately annotating genetic variants.展开更多
The abundant entities and entity-attribute relations in medical websites are important data resources for medical research.However,the medical websites are usually characterized of storing entity and attribute values ...The abundant entities and entity-attribute relations in medical websites are important data resources for medical research.However,the medical websites are usually characterized of storing entity and attribute values in different pages.To extract those data records efficiently,we propose an automatic extraction system which is related to entity and attribute relations（attributes and values）of separate storage.Our system includes following modules：（1）rich-information interactive annotation page rendering;（2）separate storage attribute relations annotating;（3）annotated relations for pattern generating and data records extracting.This paper presents the relations about the attributes which are stored in many pages by effective annotation,then generates rules for data records extraction.The experiments show that the system can not only complete attribute relations of separate storage extraction,but also be compatible with regular relation extraction,while maintaining high accuracy.展开更多
Glaucoma is an eye disease characterized by pathologically elevated intraocular pressure,optic nerve atrophy,and visual field defects,which can lead to irreversible vision loss.In recent years,the rapid development of...Glaucoma is an eye disease characterized by pathologically elevated intraocular pressure,optic nerve atrophy,and visual field defects,which can lead to irreversible vision loss.In recent years,the rapid development of artificial intelligence(AI)technology has provided new approaches for the early diagnosis and management of glaucoma.By classifying and annotating glaucoma-related images,AI models can learn and recognize the specific pathological features of glaucoma,thereby achieving automated imaging analysis and classification.Research on glaucoma imaging classification and annotation mainly involves color fundus photography(CFP),optical coherence tomography(OCT),anterior segment optical coherence tomography(AS-OCT),and ultrasound biomicroscopy(UBM)images.CFP is primarily used for the annotation of the optic cup and disc,while OCT is used for measuring and annotating the thickness of the retinal nerve fiber layer,and AS-OCT and UBM focus on the annotation of the anterior chamber angle structure and the measurement of anterior segment structural parameters.To standardize the classification and annotation of glaucoma images,enhance the quality and consistency of annotated data,and promote the clinical application of intelligent ophthalmology,this guideline has been developed.This guideline systematically elaborates on the principles,methods,processes,and quality control requirements for the classification and annotation of glaucoma images,providing standardized guidance for the classification and annotation of glaucoma images.展开更多
Natural products(NPs)have long held a significant position in various fields such as medicine,food,agriculture,and materials.The chemical space covered by NPs is extensive but often underexplored.Therefore,high-throug...Natural products(NPs)have long held a significant position in various fields such as medicine,food,agriculture,and materials.The chemical space covered by NPs is extensive but often underexplored.Therefore,high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems.Mass spectrometry(MS)has emerged as a powerful platform for the annotation and discovery of NPs.MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information.Additionally,the released annotation methodologies,based on a variety of informatics tools,continuously improve the ability to annotate the structure and properties of compounds.This review examines the current mainstream databases and annotation methodologies,focusing on their advantages and limitations.Prospects for future technological advancements are then discussed in terms of novel applications and research objectives.Through a systematic overview,this review aims to provide valuable insights and a reference for MS-based NPs annotation,thereby promoting the discovery of novel natural entities.展开更多
Understanding genetic variant functionality is essential for advancing animal genomics and precision breeding.However,the lack of comprehensive functional genomic annotations in animals limits the effectiveness of mos...Understanding genetic variant functionality is essential for advancing animal genomics and precision breeding.However,the lack of comprehensive functional genomic annotations in animals limits the effectiveness of most variant function assessment methods.In this study,we gather 1030 raw epigenomic datasets from 10 animal species and systematically annotate 7 types of key regulatory regions,creating a comprehensive functional annotation map of animal genomic variants.Our findings demonstrate that integrating variants with regulatory annotations can identify tissues and cell types underlying economic traits,underscoring the utility of these annotations in functional variant discovery.Using our functional annotations,we rank the functional potential of genetic variants and classify over 127 million candidate variants into 5 functional confidence categories,with high-confidence variants significantly enriched in eQTLs and trait-associated SNPs.Incorporating these variants into genomic prediction models can improve estimated breeding value accuracy,demonstrating their practical utility in breeding programs.To facilitate the use of our results,we develop the Integrated Functional Mutation(IFmut:http://www.ifmutants.com:8212)platform,enabling researchers to explore regulatory annotations and assess the functional potential of animal variants efficiently.Our study provides a robust framework for functional genomic annotations in farm animals,enhancing variant function assessment and breeding precision.展开更多
Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summariza...Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summarization is described. Three kernel descriptors such as gradient, shape, and color are extracted, respectively. Feature late-fusion is executed in turn by the multiple kernel learning model to obtain more discriminant image features. Absolute rank and relative rank of the tag-rank model are used to boost the key words＇ weights. A new word integration algorithm named word sequence blocks building （WSBB） is designed to create N-gram word sequences. Sentences are generated according to the N-gram word sequences and predefined templates. Experimental results show that both the BLEU-1 scores and BLEU-2 scores of the sentences are superior to those of the state-of-art baselines.展开更多
In order to implement the real-time detection of abnormality of elder and devices in an empty nest home,multi-modal joint sensors are used to collect discrete action sequences of behavior,and the improved hierarchical...In order to implement the real-time detection of abnormality of elder and devices in an empty nest home,multi-modal joint sensors are used to collect discrete action sequences of behavior,and the improved hierarchical hidden Markov model is adopted to Abstract these discrete action sequences captured by multi-modal joint sensors into an occupant’s high-level behavior—event,then structure representation models of occupant normality are modeled from large amounts of spatio-temporal data. These models are used as classifiers of normality to detect an occupant’s abnormal behavior.In order to express context information needed by reasoning and detection,multi-media ontology （MMO） is designed to annotate and reason about the media information in the smart monitoring system.A pessimistic emotion model （PEM） is improved to analyze multi-interleaving events of multi-active devices in the home.Experiments demonstrate that the PEM can enhance the accuracy and reliability for detecting active devices when these devices are in blind regions or are occlusive. The above approach has good performance in detecting abnormalities involving occupants and devices in a real-time way.展开更多
The Chinese tree shrew(Tupaia belangeri chinensis)is emerging as an important experimental animal in multiple fields of biomedical research.Comprehensive reference genome annotation for both mRNA and long non-coding R...The Chinese tree shrew(Tupaia belangeri chinensis)is emerging as an important experimental animal in multiple fields of biomedical research.Comprehensive reference genome annotation for both mRNA and long non-coding RNA(lncRNA)is crucial for developing animal models using this species.In the current study,we collected a total of 234 high-quality RNA sequencing(RNA-seq)datasets and two long-read isoform sequencing(ISO-seq)datasets and improved the annotation of our previously assembled high-quality chromosomelevel tree shrew genome.We obtained a total of 3514 newly annotated coding genes and 50576 lncRNA genes.We also characterized the tissuespecific expression patterns and alternative splicing patterns of mRNAs and lncRNAs and mapped the orthologous relationships among 11 mammalian species using the current annotated genome.We identified 144 tree shrew-specific gene families,including interleukin 6(IL6)and STT3 oligosaccharyltransferase complex catalytic subunit B(STT3B),which underwent significant changes in size.Comparison of the overall expression patterns in tissues and pathways across four species(human,rhesus monkey,tree shrew,and mouse)indicated that tree shrews are more similar to primates than to mice at the tissue-transcriptome level.Notably,the newly annotated purine rich element binding protein A(PURA)gene and the STT3B gene family showed dysregulation upon viral infection.The updated version of the tree shrew genome annotation(KIZ version 3:TS_3.0)is available at http://www.treeshrewdb.org and provides an essential reference for basic and biomedical studies using tree shrew animal models.展开更多
It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotat...It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.展开更多
Since the publication of this article,the authors have noticed that the GeneIDs from new and original genome annotations don’t match in Table S6,the correct Table S6 is given here.The authors would like to apologize ...Since the publication of this article,the authors have noticed that the GeneIDs from new and original genome annotations don’t match in Table S6,the correct Table S6 is given here.The authors would like to apologize for this error.展开更多
In industry,it is becoming common to detect and recognize industrial workpieces using deep learning methods.In this field,the lack of datasets is a big problem,and collecting and annotating datasets in this field is v...In industry,it is becoming common to detect and recognize industrial workpieces using deep learning methods.In this field,the lack of datasets is a big problem,and collecting and annotating datasets in this field is very labor intensive.The researchers need to perform dataset annotation if a dataset is generated by themselves.It is also one of the restrictive factors that the current method based on deep learning cannot expand well.At present,there are very few workpiece datasets for industrial fields,and the existing datasets are generated from ideal workpiece computer aided design(CAD)models,for which few actual workpiece images were collected and utilized.We propose an automatic industrial workpiece dataset generation method and an automatic ground truth annotation method.Included in our methods are three algorithms that we proposed:a point cloud based spatial plane segmentation algorithm to segment the workpieces in the real scene and to obtain the annotation information of the workpieces in the images captured in the real scene;a random multiple workpiece generation algorithm to generate abundant composition datasets with random rotation workpiece angles and positions;and a tangent vector based contour tracking and completion algorithm to get improved contour images.With our procedures,annotation information can be obtained using the algorithms proposed in this paper.Upon completion of the annotation process,a json format file is generated.Faster R-CNN(Faster R-convolutional neural network),SSD(single shot multibox detector)and YOLO(you only look once:unified,real-time object detection)are trained using the datasets proposed in this paper.The experimental results show the effectiveness and integrity of this dataset generation and annotation method.展开更多
This paper discusses the placement of Chinese annotation from point of view of graphics. Area Feature is classified as simple polygon, complex polygon and special polygon. For simple ones, annotations are placed along...This paper discusses the placement of Chinese annotation from point of view of graphics. Area Feature is classified as simple polygon, complex polygon and special polygon. For simple ones, annotations are placed along the longest edge. For complex ones, firstly the polygon are simplified according to close points, then the longest diagonal is gotten by comparing length, lastly, annotations are placed along long diagonal. For special ones, the polygon are partitioned into several parts by a certain rule for getting their sub\|diagonals, then their annotation are placed by means of the second.展开更多
文摘of complete genome sequences submitted directly from sequencing projects are diverse in terms of annotation strategies and update frequencies. These inconsistencies make comparative studies difficult. To allow rapid data preparation of a large number of complete genomes, automation and speed are important for genome re-annotation. Here we introduce an open-source rapid genome re-annotation software system, Restauro-G, specialized for bacterial genomes. Restauro-G re-annotates a genome by similarity searches utilizing the BLASTLike Alignment Tool, referring to protein databases such as UniProt KB, NCBI nr, NCBI COGs, Pfam, and PSORTb. Re-annotation by Restauro-G achieved over 98% accuracy for most bacterial chromosomes in comparison with the original manually curated annotation of EMBL releases. Restauro-G was developed in the generic bioinformatics workbench G-language Genome Analysis Environment and is distributed at http：//restauro-g.iab.keio.ac.jp/ under the GNU General Public License.
基金supported by funds from the National Key R&D Program of China (2016YFC0901603)the China 863 Program (2015AA020108)+1 种基金the State Key Laboratory of Protein and Plant Gene Researchsupported in part by the National Program for Support of Top-notch Young Professionals
文摘Understanding the functional effects of genetic variants is crucial in modern genomics and genetics. Transcription factor binding sites （TFBSs） are one of the most important cis-regulatory elements. While multiple tools have been developed to assess functional effects of genetic variants at TFBSs, they usually assume that each variant works in isolation and neglect the potential ＂interference＂ among multiple variants within the same TFBS. In this study, we presented COPE-TFBS （Context-Oriented Predictor for variant Effect on Transcription Factor Binding Site）, a novel method that considers sequence context to accurately predict variant effects on TFBSs. We systematically re-analyzed the sequencing data from both the 1000 Genomes Project and the Genotype-Tissue Expression （GTEx） Project via COPE-TFBS, and identified numbers of novel TFBSs, transformed TFBSs and discordantly annotated TFBSs resulting from multiple variants, further highlighting the necessity of sequence context in accurately annotating genetic variants.
基金Supported by the Natural Science Foundation of Hubei Province(2013CFB334)
文摘The abundant entities and entity-attribute relations in medical websites are important data resources for medical research.However,the medical websites are usually characterized of storing entity and attribute values in different pages.To extract those data records efficiently,we propose an automatic extraction system which is related to entity and attribute relations（attributes and values）of separate storage.Our system includes following modules：（1）rich-information interactive annotation page rendering;（2）separate storage attribute relations annotating;（3）annotated relations for pattern generating and data records extracting.This paper presents the relations about the attributes which are stored in many pages by effective annotation,then generates rules for data records extraction.The experiments show that the system can not only complete attribute relations of separate storage extraction,but also be compatible with regular relation extraction,while maintaining high accuracy.
基金Supported by Guangdong Basic and Applied Basic Research Foundation(No.2025A1515011627)San Ming Project of Medicine in Shenzhen(No.SZSM202311012).
文摘Glaucoma is an eye disease characterized by pathologically elevated intraocular pressure,optic nerve atrophy,and visual field defects,which can lead to irreversible vision loss.In recent years,the rapid development of artificial intelligence(AI)technology has provided new approaches for the early diagnosis and management of glaucoma.By classifying and annotating glaucoma-related images,AI models can learn and recognize the specific pathological features of glaucoma,thereby achieving automated imaging analysis and classification.Research on glaucoma imaging classification and annotation mainly involves color fundus photography(CFP),optical coherence tomography(OCT),anterior segment optical coherence tomography(AS-OCT),and ultrasound biomicroscopy(UBM)images.CFP is primarily used for the annotation of the optic cup and disc,while OCT is used for measuring and annotating the thickness of the retinal nerve fiber layer,and AS-OCT and UBM focus on the annotation of the anterior chamber angle structure and the measurement of anterior segment structural parameters.To standardize the classification and annotation of glaucoma images,enhance the quality and consistency of annotated data,and promote the clinical application of intelligent ophthalmology,this guideline has been developed.This guideline systematically elaborates on the principles,methods,processes,and quality control requirements for the classification and annotation of glaucoma images,providing standardized guidance for the classification and annotation of glaucoma images.
基金supported by the National Natural Science Foundation of China(Nos.82274064,82374026,and 82204591)。
文摘Natural products(NPs)have long held a significant position in various fields such as medicine,food,agriculture,and materials.The chemical space covered by NPs is extensive but often underexplored.Therefore,high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems.Mass spectrometry(MS)has emerged as a powerful platform for the annotation and discovery of NPs.MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information.Additionally,the released annotation methodologies,based on a variety of informatics tools,continuously improve the ability to annotate the structure and properties of compounds.This review examines the current mainstream databases and annotation methodologies,focusing on their advantages and limitations.Prospects for future technological advancements are then discussed in terms of novel applications and research objectives.Through a systematic overview,this review aims to provide valuable insights and a reference for MS-based NPs annotation,thereby promoting the discovery of novel natural entities.
基金supported by the National Natural Science Foundation of China(32341051)the grant from Department of Agriculture and Rural Affairs of Hubei Province(HBZY2023B006-02)+2 种基金the National Funding(2023ZD04050)the National Natural Science Foundation of China Outstanding Youth(32125035)the National Key R&D Young Scientists Project(2022YFD1302000).
文摘Understanding genetic variant functionality is essential for advancing animal genomics and precision breeding.However,the lack of comprehensive functional genomic annotations in animals limits the effectiveness of most variant function assessment methods.In this study,we gather 1030 raw epigenomic datasets from 10 animal species and systematically annotate 7 types of key regulatory regions,creating a comprehensive functional annotation map of animal genomic variants.Our findings demonstrate that integrating variants with regulatory annotations can identify tissues and cell types underlying economic traits,underscoring the utility of these annotations in functional variant discovery.Using our functional annotations,we rank the functional potential of genetic variants and classify over 127 million candidate variants into 5 functional confidence categories,with high-confidence variants significantly enriched in eQTLs and trait-associated SNPs.Incorporating these variants into genomic prediction models can improve estimated breeding value accuracy,demonstrating their practical utility in breeding programs.To facilitate the use of our results,we develop the Integrated Functional Mutation(IFmut:http://www.ifmutants.com:8212)platform,enabling researchers to explore regulatory annotations and assess the functional potential of animal variants efficiently.Our study provides a robust framework for functional genomic annotations in farm animals,enhancing variant function assessment and breeding precision.
基金The National Natural Science Foundation of China(No.61133012)the Humanity and Social Science Foundation of the Ministry of Education(No.12YJCZH274)+1 种基金the Humanity and Social Science Foundation of Jiangxi Province(No.XW1502,TQ1503)the Science and Technology Project of Jiangxi Science and Technology Department(No.20121BBG70050,20142BBG70011)
文摘Dealing with issues such as too simple image features and word noise inference in product image sentence anmotation, a product image sentence annotation model focusing on image feature learning and key words summarization is described. Three kernel descriptors such as gradient, shape, and color are extracted, respectively. Feature late-fusion is executed in turn by the multiple kernel learning model to obtain more discriminant image features. Absolute rank and relative rank of the tag-rank model are used to boost the key words＇ weights. A new word integration algorithm named word sequence blocks building （WSBB） is designed to create N-gram word sequences. Sentences are generated according to the N-gram word sequences and predefined templates. Experimental results show that both the BLEU-1 scores and BLEU-2 scores of the sentences are superior to those of the state-of-art baselines.
基金The National Natural Science Foundation of China(No.60773110)the Youth Education Fund of Hunan Province(No.07B014)
文摘In order to implement the real-time detection of abnormality of elder and devices in an empty nest home,multi-modal joint sensors are used to collect discrete action sequences of behavior,and the improved hierarchical hidden Markov model is adopted to Abstract these discrete action sequences captured by multi-modal joint sensors into an occupant’s high-level behavior—event,then structure representation models of occupant normality are modeled from large amounts of spatio-temporal data. These models are used as classifiers of normality to detect an occupant’s abnormal behavior.In order to express context information needed by reasoning and detection,multi-media ontology （MMO） is designed to annotate and reason about the media information in the smart monitoring system.A pessimistic emotion model （PEM） is improved to analyze multi-interleaving events of multi-active devices in the home.Experiments demonstrate that the PEM can enhance the accuracy and reliability for detecting active devices when these devices are in blind regions or are occlusive. The above approach has good performance in detecting abnormalities involving occupants and devices in a real-time way.
基金This study was supported by the National Natural Science Foundation of China(U1902215 to Y.G.Y.and 31970542 to Y.F.)Chinese Academy of Sciences(Light of West China Program xbzg-zdsys-201909 to Y.G.Y.)Yunnan Province(202001AS070023 and 2018FB046 to D.D.Y.and 202002AA100007 to Y.G.Y.)。
文摘The Chinese tree shrew(Tupaia belangeri chinensis)is emerging as an important experimental animal in multiple fields of biomedical research.Comprehensive reference genome annotation for both mRNA and long non-coding RNA(lncRNA)is crucial for developing animal models using this species.In the current study,we collected a total of 234 high-quality RNA sequencing(RNA-seq)datasets and two long-read isoform sequencing(ISO-seq)datasets and improved the annotation of our previously assembled high-quality chromosomelevel tree shrew genome.We obtained a total of 3514 newly annotated coding genes and 50576 lncRNA genes.We also characterized the tissuespecific expression patterns and alternative splicing patterns of mRNAs and lncRNAs and mapped the orthologous relationships among 11 mammalian species using the current annotated genome.We identified 144 tree shrew-specific gene families,including interleukin 6(IL6)and STT3 oligosaccharyltransferase complex catalytic subunit B(STT3B),which underwent significant changes in size.Comparison of the overall expression patterns in tissues and pathways across four species(human,rhesus monkey,tree shrew,and mouse)indicated that tree shrews are more similar to primates than to mice at the tissue-transcriptome level.Notably,the newly annotated purine rich element binding protein A(PURA)gene and the STT3B gene family showed dysregulation upon viral infection.The updated version of the tree shrew genome annotation(KIZ version 3:TS_3.0)is available at http://www.treeshrewdb.org and provides an essential reference for basic and biomedical studies using tree shrew animal models.
基金the support of the National Natural Science Foundation of China under Grant No.60673023,60433020,10501017,3040016the European Commission for TH/Asia Link/010 under Grant No.111084.
文摘It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.
文摘Since the publication of this article,the authors have noticed that the GeneIDs from new and original genome annotations don’t match in Table S6,the correct Table S6 is given here.The authors would like to apologize for this error.
文摘In industry,it is becoming common to detect and recognize industrial workpieces using deep learning methods.In this field,the lack of datasets is a big problem,and collecting and annotating datasets in this field is very labor intensive.The researchers need to perform dataset annotation if a dataset is generated by themselves.It is also one of the restrictive factors that the current method based on deep learning cannot expand well.At present,there are very few workpiece datasets for industrial fields,and the existing datasets are generated from ideal workpiece computer aided design(CAD)models,for which few actual workpiece images were collected and utilized.We propose an automatic industrial workpiece dataset generation method and an automatic ground truth annotation method.Included in our methods are three algorithms that we proposed:a point cloud based spatial plane segmentation algorithm to segment the workpieces in the real scene and to obtain the annotation information of the workpieces in the images captured in the real scene;a random multiple workpiece generation algorithm to generate abundant composition datasets with random rotation workpiece angles and positions;and a tangent vector based contour tracking and completion algorithm to get improved contour images.With our procedures,annotation information can be obtained using the algorithms proposed in this paper.Upon completion of the annotation process,a json format file is generated.Faster R-CNN(Faster R-convolutional neural network),SSD(single shot multibox detector)and YOLO(you only look once:unified,real-time object detection)are trained using the datasets proposed in this paper.The experimental results show the effectiveness and integrity of this dataset generation and annotation method.
文摘This paper discusses the placement of Chinese annotation from point of view of graphics. Area Feature is classified as simple polygon, complex polygon and special polygon. For simple ones, annotations are placed along the longest edge. For complex ones, firstly the polygon are simplified according to close points, then the longest diagonal is gotten by comparing length, lastly, annotations are placed along long diagonal. For special ones, the polygon are partitioned into several parts by a certain rule for getting their sub\|diagonals, then their annotation are placed by means of the second.
