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Found 2 papers, 1 papers with code
Cluster-Based Learning from Weakly Labeled Bags in Digital Pathology
To alleviate the burden of gathering detailed expert annotations when training deep neural networks, we propose a weakly supervised learning approach to recognize metastases in microscopic images of breast lymph nodes.
Transitioning between Convolutional and Fully Connected Layers in Neural Networks
Digital pathology has advanced substantially over the last decade however tumor localization continues to be a challenging problem due to highly complex patterns and textures in the underlying tissue bed.
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