Deep Collocative Learning for Immunofixation Electrophoresis Image Analysis
Published in IEEE Transactions on Medical Imaging, 2021
We proposed a new method called collocative learning, in which a collocative tensor has been constructed to transform binary relations into unary relations that are compatible with conventional deep networks, and a location-label-free method that utilizes Grad-CAM saliency maps for evidence backtracking has been proposed for accurate localization. In addition, we have proposed Coached Attention Gates that can regulate the inference of the learning to be more consistent with human logic and thus support the evidence backtracking.
Recommended citation: Xiao-Yong Wei, Zhen-Qun Yang, Xu-Lu Zhang, et al., (2021). "Deep Collocative Learning for Immunofixation Electrophoresis Image Analysis." IEEE Transactions on Medical Imaging.
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