3 papers
cs.CV2025
Fake & Square: Training Self-Supervised Vision Transformers with Synthetic Data and Synthetic Hard Negatives
Nikolaos Giakoumoglou, Nikos Giakoumoglou, Andreas Floros +2
This paper does not introduce a new method per se. Instead, we build on existing self-supervised learning approaches for vision, drawing inspiration from the adage "fake it till yo…
cs.CV2025
Unsupervised Training of Vision Transformers with Synthetic Negatives
Nikolaos Giakoumoglou, Nikos Giakoumoglou, Andreas Floros +2
This paper does not introduce a novel method per se. Instead, we address the neglected potential of hard negative samples in self-supervised learning. Previous works explored synth…
eess.IV2025
Comparing ImageNet Pre-training with Digital Pathology Foundation Models for Whole Slide Image-Based Survival Analysis
Kleanthis Marios Papadopoulos, Tania Stathaki
The abundance of information present in Whole Slide Images (WSIs) renders them an essential tool for survival analysis. Several Multiple Instance Learning frameworks proposed for t…