Search Results for author: Joseph DiPalma

Found 3 papers, 1 papers with code

Improving Representation Learning for Histopathologic Images with Cluster Constraints

1 code implementation ICCV 2023 Weiyi Wu, Chongyang Gao, Joseph DiPalma, Soroush Vosoughi, Saeed Hassanpour

This framework aims for transferable representation learning and semantically meaningful clustering by synergizing invariance loss and clustering loss in WSI analysis.

Clustering Representation Learning +1

Resolution-Based Distillation for Efficient Histology Image Classification

no code implementations11 Jan 2021 Joseph DiPalma, Arief A. Suriawinata, Laura J. Tafe, Lorenzo Torresani, Saeed Hassanpour

Our results show that a combination of KD and self-supervision allows the student model to approach, and in some cases, surpass the classification accuracy of the teacher, while being much more efficient.

Classification Computational Efficiency +3

HistoPerm: A Permutation-Based View Generation Approach for Improving Histopathologic Feature Representation Learning

no code implementations13 Sep 2022 Joseph DiPalma, Lorenzo Torresani, Saeed Hassanpour

These findings suggest that HistoPerm can be a valuable tool for improving representation learning of histopathology features when access to labeled data is limited and can lead to whole-slide classification results that are comparable to or superior to fully-supervised methods.

Classification Representation Learning

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