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20152024
most citedDecentralized Federated Learning through Proxy Model Sharing

160 citations · 607 across the 73 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.CV2022

Learning Binary and Sparse Permutation-Invariant Representations for Fast and Memory Efficient Whole Slide Image Search

Sobhan Hemati, Shivam Kalra, Morteza Babaie +1

Learning suitable Whole slide images (WSIs) representations for efficient retrieval systems is a non-trivial task. The WSI embeddings obtained from current methods are in Euclidean…

cs.CR2022

Cluster Based Secure Multi-Party Computation in Federated Learning for Histopathology Images

S. Maryam Hosseini, Milad Sikaroudi, Morteza Babaei +1

Federated learning (FL) is a decentralized method enabling hospitals to collaboratively learn a model without sharing private patient data for training. In FL, participant hospital…

cs.LG2022★ 2 cited

Monitoring Shortcut Learning using Mutual Information

Mohammed Adnan, Yani Ioannou, Chuan-Yung Tsai +3

The failure of deep neural networks to generalize to out-of-distribution data is a well-known problem and raises concerns about the deployment of trained networks in safety-critica…

eess.IV2022

Hospital-Agnostic Image Representation Learning in Digital Pathology

Milad Sikaroudi, Shahryar Rahnamayan, H. R. Tizhoosh

Whole Slide Images (WSIs) in digital pathology are used to diagnose cancer subtypes. The difference in procedures to acquire WSIs at various trial sites gives rise to variability i…

eess.IV2022★ 1 cited

Learning to Predict RNA Sequence Expressions from Whole Slide Images with Applications for Search and Classification

Amir Safarpoor, Jason D. Hipp, H. R. Tizhoosh

Deep learning methods are widely applied in digital pathology to address clinical challenges such as prognosis and diagnosis. As one of the most recent applications, deep models ha…

cs.CV2022★ 3 cited

LILE: Look In-Depth before Looking Elsewhere -- A Dual Attention Network using Transformers for Cross-Modal Information Retrieval in Histopathology Archives

Danial Maleki, H. R Tizhoosh

The volume of available data has grown dramatically in recent years in many applications. Furthermore, the age of networks that used multiple modalities separately has practically…