Showing 1–20 of 47 results
/ Date/ Name
Feb 14, 2018Morphologic for knowledge dynamics: revision, fusion, abductionFeb 26, 2015A finite basis theorem for the description logic ${\cal ALC}$Dec 24, 2019TRADI: Tracking deep neural network weight distributions for uncertainty estimationMar 19, 2019Max-plus Operators Applied to Filter Selection and Model Pruning in Neural NetworksFeb 26, 2015Relaxation-based revision operators in description logicsFeb 8, 2015Belief Revision, Minimal Change and Relaxation: A General Framework based on Satisfaction Systems, and Applications to Description LogicsMar 8, 2023Morpho-logic from a Topos Perspective: Application to symbolic AIMay 4, 2020Abstract Mathematical morphology based on structuring element: Application to morpho-logicMar 20, 2019Part-based approximations for morphological operators using asymmetric auto-encodersMar 13, 2020Flexible and Context-Specific AI Explainability: A Multidisciplinary ApproachMar 20, 2020Investigating Image Applications Based on Spatial-Frequency Transform and Deep Learning TechniquesJan 16, 2017Classification of MRI data using Deep Learning and Gaussian Process-based Model SelectionMar 5, 2018Explanatory relations in arbitrary logics based on satisfaction systems, cutting and retractionOct 16, 2017Dual Logic Concepts based on Mathematical Morphology in Stratified Institutions: Applications to Spatial ReasoningDec 19, 2016Exploring Structure for Long-Term Tracking of Multiple Objects in Sports VideosMay 12, 2022Real-time Virtual-Try-On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable RenderersJun 17, 2021Knowledge distillation from multi-modal to mono-modal segmentation networksSep 18, 2025Visionerves: Automatic and Reproducible Hybrid AI for Peripheral Nervous System Recognition Applied to Endometriosis CasesAug 18, 2023Decoupled conditional contrastive learning with variable metadata for prostate lesion detectionSep 29, 2020Improving Interpretability for Computer-aided Diagnosis tools on Whole Slide Imaging with Multiple Instance Learning and Gradient-based Explanations