Interpreting Convolutional Neural Networks by Explaining Their Predictions. - Toon Meynen; Hamed Behzadi-Khormouji; José Oramas (ICIP, 2023)

FICNN: A Framework for the Interpretation of Deep Convolutional Neural Networks. - Hamed Behzadi-Khormouji; José Oramas (CoRR, 2023)

Deep Learning for Healthcare: A Web-Microservices System Ready for Chest Pathology Detection. - Sebastián Quevedo; Hamed Behzadi-Khormouji; Federico Domínguez; Enrique Peláez (WorldCIST (2), 2024)

Deep Model Interpretation with Limited Data : A Coreset-based Approach. - Hamed Behzadi-Khormouji; José Oramas (CoRR, 2024)

Automatic extraction of lightweight and efficient neural network architecture of heavy convolutional architectures to predict microsatellite instability from hematoxylin and eosin histology in gastric cancer. - Habib Rostami; Maryam Ashkpour; Hamed Behzadi-Khormouji; Maral Mokhtari; Armin Khayati; Ahmad Keshavarz; Saeed Talatian Azad; Yahya Tabesh (Neural Comput. Appl., 2024)