3 papers
q-bio.QM2025
Pathology Foundation Models are Scanner Sensitive: Benchmark and Mitigation with Contrastive ScanGen Loss
Gianluca Carloni, Biagio Brattoli, Seongho Keum +4
Computational pathology (CPath) has shown great potential in mining actionable insights from Whole Slide Images (WSIs). Deep Learning (DL) has been at the center of modern CPath, a…
cs.CV2025
Human-aligned Deep Learning: Explainability, Causality, and Biological Inspiration
Gianluca Carloni
This work aligns deep learning (DL) with human reasoning capabilities and needs to enable more efficient, interpretable, and robust image classification. We approach this from thre…
cs.CV2024
Connectivity-Inspired Network for Context-Aware Recognition
Gianluca Carloni, Sara Colantonio
The aim of this paper is threefold. We inform the AI practitioner about the human visual system with an extensive literature review; we propose a novel biologically motivated neura…