Recent Studies from University of Nottingham Add New Data to Computational Intel ligence (Low-contrast Medical Image Segmentation Via Transformer and Boundary Pe rception)
诺丁汉大学最近的研究为计算智能(通过Transformer和Boundary Pe reception进行低对比度医学图像分割)增加了新的数据
Recent Studies from University of Nottingham Add New Data to Computational Intel ligence (Low-contrast Medical Image Segmentation Via Transformer and Boundary Pe rception)
诺丁汉大学最近的研究为计算智能(通过Transformer和Boundary Pe reception进行低对比度医学图像分割)增加了新的数据
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Machine Learning - Comp utational Intelligence is now available. According to news originating from Ning bo, People's Republic of China, by NewsRx correspondents, research stated, "Low- contrast medical image segmentation is a challenging task that requires full use of local details and global context. However, existing convolutional neural net works (CNNs) cannot fully exploit global information due to limited receptive fi elds and local weight sharing." Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
Key words
Ningbo/People's Republic of China/Asia/Computational Intelligence/Machine Learning/University of Nottingham
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