IET Computer Vision

期刊简介：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 organisationRepresentation, analysis and matching of 2D and 3D shapeShape-from-XObject recognitionImage understandingLearning with visual inputsMotion analysis and object trackingMultiview scene analysisCognitive approaches in low, mid and high level visionControl in visual systemsColour, reflectance and lightStatistical and probabilistic modelsFace and gestureSurveillanceBiometrics and securityRoboticsVehicle guidanceAutomatic model aquisitionMedical image analysis and understandingAerial scene analysis and remote sensingDeep learning models in computer visionBoth 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.pdfComputer Vision for the Creative Industries - https://digital-library.theiet.org/files/IET_CVI_CVCI.pdf

【译文】IET计算机视觉寻求计算机视觉广泛领域的原创研究论文。该期刊的愿景是发表最高质量的相关且具有时效性的研究成果，同时不忘那些旨在开拓新视野并为计算机视觉未来研究方向设定议程的研究成果。IET计算机视觉欢迎以下主题的投稿：基于生物学和感知的低级视觉方法（特征检测等）；感知分组和组织；二维和三维形状的表示、分析和匹配；从X中获取形状；物体识别；图像理解；基于视觉输入的学习；运动分析和目标跟踪；多视图场景分析；低、中、高级视觉中的认知方法；视觉系统中的控制；颜色、反射和光；统计和概率模型；人脸和手势；监控；生物识别和安全；机器人；车辆引导；自动模型获取；医学图像分析和理解；空中场景分析和遥感；计算机视觉中的深度学习模型；欢迎方法导向和应用导向的论文。提交的稿件应包括对文献的详细和分析性回顾，对原创研究及其方法、其彻底的实验评估，以及最后但并非最不重要的是，与相关和最先进方法的比较评估。不符合这些最低要求的稿件可能会被退回给作者而不会被送审。