Erratum: Integration graph attention network and multi-centre constrained loss for cross-modality person re-identification

IF 1.5 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

IET Computer Vision Pub Date : 2023-06-01 DOI:10.1049/cvi2.12210

引用次数: 0

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更正:跨模态人再识别的整合图、注意网络和多中心约束损失

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来源期刊

IET Computer Vision 工程技术-工程：电子与电气

CiteScore

3.30

自引率

11.80%

发文量

审稿时长

3.4 months

期刊介绍： IET Computer Vision seeks original research papers in a wide range of areas of computer vision. The vision of the journal is to publish the highest quality research work that is relevant and topical to the field, but not forgetting those works that aim to introduce new horizons and set the agenda for future avenues of research in computer vision. IET Computer Vision welcomes submissions on the following topics: Biologically and perceptually motivated approaches to low level vision (feature detection, etc.); Perceptual grouping and organisation Representation, analysis and matching of 2D and 3D shape Shape-from-X Object recognition Image understanding Learning with visual inputs Motion analysis and object tracking Multiview scene analysis Cognitive approaches in low, mid and high level vision Control in visual systems Colour, reflectance and light Statistical and probabilistic models Face and gesture Surveillance Biometrics and security Robotics Vehicle guidance Automatic model aquisition Medical image analysis and understanding Aerial scene analysis and remote sensing Deep learning models in computer vision Both methodological and applications orientated papers are welcome. Manuscripts submitted are expected to include a detailed and analytical review of the literature and state-of-the-art exposition of the original proposed research and its methodology, its thorough experimental evaluation, and last but not least, comparative evaluation against relevant and state-of-the-art methods. Submissions not abiding by these minimum requirements may be returned to authors without being sent to review. Special Issues Current Call for Papers: Computer Vision for Smart Cameras and Camera Networks - https://digital-library.theiet.org/files/IET_CVI_SC.pdf Computer Vision for the Creative Industries - https://digital-library.theiet.org/files/IET_CVI_CVCI.pdf