14 citations · 26 across the 3 of their papers we have counts for
3 papers
eess.IV2019★ 10 cited
Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types
Shahira Abousamra, Le Hou, Rajarsi Gupta +7
Deep learning classifiers for characterization of whole slide tissue morphology require large volumes of annotated data to learn variations across different tissue and cancer types…
cs.CV2017★ 2 cited
Center-Focusing Multi-task CNN with Injected Features for Classification of Glioma Nuclear Images
Veda Murthy, Le Hou, Dimitris Samaras +2
Classifying the various shapes and attributes of a glioma cell nucleus is crucial for diagnosis and understanding the disease. We investigate automated classification of glioma nuc…
cs.CV2016★ 14 cited
Neural Networks with Smooth Adaptive Activation Functions for Regression
Le Hou, Dimitris Samaras, Tahsin M. Kurc +2
In Neural Networks (NN), Adaptive Activation Functions (AAF) have parameters that control the shapes of activation functions. These parameters are trained along with other paramete…