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机译:从多样性和更难的样品中学习:改善基于CNN的计算机生成图像的概括
Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit NLPR Beijing 100190 Peoples R China|Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China|Univ Grenoble Alpes GIPSA Lab Grenoble INP CNRS F-38000 Grenoble France;
Univ Grenoble Alpes GIPSA Lab Grenoble INP CNRS F-38000 Grenoble France;
Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit NLPR Beijing 100190 Peoples R China|Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China;
Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit NLPR Beijing 100190 Peoples R China|Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China;
Univ Grenoble Alpes GIPSA Lab Grenoble INP CNRS F-38000 Grenoble France;
Image forensics; Computer-generated image; Convolutional neural network; Generalization; Negative samples;
机译:基于CNN的转移学习从胸部X射线图像检测Covid-19
机译:学习VHR遥感图像中船舶检测的强大基于CNN的旋转不敏感模型
机译:由采样计算机生成的全息图重建的输出图像的分辨率和强度分布
机译:基于CNN的黑白图像对称轴检测的改进方法
机译:使用采样分集从多个欠采样图像中实现盲超分辨率。
机译:夜间入侵预警系统基于CNN的红外图像人检测
机译:从多样性和更难的样品中学习:改善基于CNN的计算机生成图像的概括
机译:基于感知的改进计算机生成图像的技术