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ICA-Net:improving class activation for weakly supervised semantic segmentation via joint contrastive and simulation learning
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作者 YE Zhuang LIU Ruyu SUN Bo 《Optoelectronics Letters》 2025年第3期188-192,共5页
In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can... In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can provide a more reliable approach in these situations.Current popular approaches mainly adopt the classification-based class activation maps(CAM)as initial pseudo labels to solve the task. 展开更多
关键词 high resolution imaging supervised learning class activation maps joint contrastive simulation learning special spectral ranges weakly supervised learning OPTOELECTRONICS
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