4 citations · 13 across the 15 of their papers we have counts for
16 papers
INTERACT-CMIL: Multi-Task Shared Learning and Inter-Task Consistency for Conjunctival Melanocytic Intraepithelial Lesion Grading
Mert Ikinci, Luna Toma, Karin U. Loeffler +6
Accurate grading of Conjunctival Melanocytic Intraepithelial Lesions (CMIL) is essential for treatment and melanoma prediction but remains difficult due to subtle morphological cue…
DeepAf: One-Shot Spatiospectral Auto-Focus Model for Digital Pathology
Yousef Yeganeh, Maximilian Frantzen, Michael Lee +3
While Whole Slide Imaging (WSI) scanners remain the gold standard for digitizing pathology samples, their high cost limits accessibility in many healthcare settings. Other low-cost…
Stress-Aware Resilient Neural Training
Ashkan Shakarami, Yousef Yeganeh, Azade Farshad +3
This paper introduces Stress-Aware Learning, a resilient neural training paradigm in which deep neural networks dynamically adjust their optimization behavior - whether under stabl…
Unit-Based Histopathology Tissue Segmentation via Multi-Level Feature Representation
Ashkan Shakarami, Azade Farshad, Yousef Yeganeh +4
We propose UTS, a unit-based tissue segmentation framework for histopathology that classifies each fixed-size 32 * 32 tile, rather than each pixel, as the segmentation unit. This a…
VeLU: Variance-enhanced Learning Unit for Deep Neural Networks
Ashkan Shakarami, Yousef Yeganeh, Azade Farshad +3
Activation functions play a critical role in deep neural networks by shaping gradient flow, optimization stability, and generalization. While ReLU remains widely used due to its si…
Conformable Convolution for Topologically Aware Learning of Complex Anatomical Structures
Yousef Yeganeh, Rui Xiao, Goktug Guvercin +2
While conventional computer vision emphasizes pixel-level and feature-based objectives, medical image analysis of intricate biological structures necessitates explicit representati…