Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection.However,small objects are difficult to detect accurately because they contain les...Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection.However,small objects are difficult to detect accurately because they contain less information.Many current methods,particularly those based on Feature Pyramid Network(FPN),address this challenge by leveraging multi-scale feature fusion.However,existing FPN-based methods often suffer from inadequate feature fusion due to varying resolutions across different layers,leading to suboptimal small object detection.To address this problem,we propose the Two-layerAttention Feature Pyramid Network(TA-FPN),featuring two key modules:the Two-layer Attention Module(TAM)and the Small Object Detail Enhancement Module(SODEM).TAM uses the attention module to make the network more focused on the semantic information of the object and fuse it to the lower layer,so that each layer contains similar semantic information,to alleviate the problem of small object information being submerged due to semantic gaps between different layers.At the same time,SODEM is introduced to strengthen the local features of the object,suppress background noise,enhance the information details of the small object,and fuse the enhanced features to other feature layers to ensure that each layer is rich in small object information,to improve small object detection accuracy.Our extensive experiments on challenging datasets such as Microsoft Common Objects inContext(MSCOCO)and Pattern Analysis Statistical Modelling and Computational Learning,Visual Object Classes(PASCAL VOC)demonstrate the validity of the proposedmethod.Experimental results show a significant improvement in small object detection accuracy compared to state-of-theart detectors.展开更多
法医DNA分型的遗传标记经历了可变数目串联重复(variable number of tandem repeat,VNTR)序列和短串联重复(short tandem repeat,STR)序列。随着测序技术的产生,出现了第三代遗传标记,因其基因座通常只有两个等位基因,故又被称为二等位...法医DNA分型的遗传标记经历了可变数目串联重复(variable number of tandem repeat,VNTR)序列和短串联重复(short tandem repeat,STR)序列。随着测序技术的产生,出现了第三代遗传标记,因其基因座通常只有两个等位基因,故又被称为二等位基因遗传标记,主要包括单核苷酸多态性(single nucleotide polymorphism,SNP)和插入/缺失(insertion/deletion,In Del)。由DNA片段插入或缺失形成的DNA长度多态性In Del遗传标记分布于整个基因组中,数目众多,兼具STR和SNP遗传标记的优势,现已应用于遗传学、人类学等领域。本文主要对In Del遗传标记在法医学领域的研究进展进行综述,旨在回顾和总结近年来的主要研究成果并为后续研究提供参考。展开更多
文摘Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection.However,small objects are difficult to detect accurately because they contain less information.Many current methods,particularly those based on Feature Pyramid Network(FPN),address this challenge by leveraging multi-scale feature fusion.However,existing FPN-based methods often suffer from inadequate feature fusion due to varying resolutions across different layers,leading to suboptimal small object detection.To address this problem,we propose the Two-layerAttention Feature Pyramid Network(TA-FPN),featuring two key modules:the Two-layer Attention Module(TAM)and the Small Object Detail Enhancement Module(SODEM).TAM uses the attention module to make the network more focused on the semantic information of the object and fuse it to the lower layer,so that each layer contains similar semantic information,to alleviate the problem of small object information being submerged due to semantic gaps between different layers.At the same time,SODEM is introduced to strengthen the local features of the object,suppress background noise,enhance the information details of the small object,and fuse the enhanced features to other feature layers to ensure that each layer is rich in small object information,to improve small object detection accuracy.Our extensive experiments on challenging datasets such as Microsoft Common Objects inContext(MSCOCO)and Pattern Analysis Statistical Modelling and Computational Learning,Visual Object Classes(PASCAL VOC)demonstrate the validity of the proposedmethod.Experimental results show a significant improvement in small object detection accuracy compared to state-of-theart detectors.
文摘法医DNA分型的遗传标记经历了可变数目串联重复(variable number of tandem repeat,VNTR)序列和短串联重复(short tandem repeat,STR)序列。随着测序技术的产生,出现了第三代遗传标记,因其基因座通常只有两个等位基因,故又被称为二等位基因遗传标记,主要包括单核苷酸多态性(single nucleotide polymorphism,SNP)和插入/缺失(insertion/deletion,In Del)。由DNA片段插入或缺失形成的DNA长度多态性In Del遗传标记分布于整个基因组中,数目众多,兼具STR和SNP遗传标记的优势,现已应用于遗传学、人类学等领域。本文主要对In Del遗传标记在法医学领域的研究进展进行综述,旨在回顾和总结近年来的主要研究成果并为后续研究提供参考。
