机译:DD-ConsficaN:通过双判别循环循环一致的生成对抗网络取消配对图像去吸附
Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201610 Peoples R China;
Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201610 Peoples R China;
Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201610 Peoples R China;
Univ Washington Dept Elect Engn Seattle WA 98195 USA;
Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201610 Peoples R China;
Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201610 Peoples R China;
Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201610 Peoples R China;
Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201610 Peoples R China;
Haze removal; Generative adversarial network;
机译:DD-CycleGAN:通过双鉴别器周期一致的生成对抗网络进行不成对的图像去雾
机译:使用未配对的生成对抗性网络去吸引白线视网膜图像
机译:CBCT校正使用循环一致的生成对抗网络和未配对的训练来实现光子和质子剂量计算
机译:通过循环一致的生成对抗网络过水的潜水图像去吸附
机译:使用条件生成对抗性网络产生核染色图像的语义分割
机译:基于先验图像信息的周期一致生成对抗网络的不成对小剂量CT降噪网络
机译:基于循环一致的生成对冲网络的未成对低剂量CT去噪网络,具有先前的图像信息