2 papers
cs.CV2026
Explaining Digital Pathology Models via Clustering Activations
Adam Bajger, Jan Obdržálek, VojtÄch Kůr +4
We present a clustering-based explainability technique for digital pathology models based on convolutional neural networks. Unlike commonly used methods based on saliency maps, suc…
cs.CV2025
LLEXICORP: End-user Explainability of Convolutional Neural Networks
VojtÄch Kůr, Adam Bajger, Adam KukuÄka +3
Convolutional neural networks (CNNs) underpin many modern computer vision systems. With applications ranging from common to critical areas, a need to explain and understand the mod…