Deep Learning
Publicaties voor trefwoord "Deep Learning"
2024
| , en , Explanation of Deep Learning Models via Logic Rules Enhanced by Embeddings Analysis, and Probabilistic Models, in: Post-proceedings of the 6th International Workshop on EXplainable and TRAnsparent AI and Multi-Agent Systems, 2024 |
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2023
| en , Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects, in: ICCV 2023 Proceedings, 2023 |
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| , , , , , , en , Development of an artificial intelligence-based method for the diagnosis of the severity of myxomatous mitral valve disease from canine chest radiographs (2023), in: Frontiers in Veterinary Science |
| , en , Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning (2023), in: IEEE Transactions on Medical Imaging, 42:3 |
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2022
| , , , , en , Deep Learning-based Framework for Automatic Cranial Defect Reconstruction and Implant Modeling (2022), in: Computer Methods and Programs in Biomedicine, 226 |
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2021
| , , , , en , Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability, in: MICCAI 2021, Springer, 2021 |
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2019
| , en , Interpreting intentionally flawed models with linear probes, in: ICCV workshop on statistical deep learning in computer vision, Seoul, Korea, 2019 |
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| , en , Visualizing and interpreting feature reuse of pretrained CNNs for histopathology, in: IMVIP 2019, Dublin, Ireland, 2019 |
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2018
| , en , A Deep Learning Mechanism for Efficient Information Dissemination in Vehicular Floating Content (2018), in: arXiv |
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| , , en , Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content, in: MICCAI 2018 - Computational Pathology Workshop (COMPAY), Granada, Spain, 2018 |
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, en , Regression Concept Vectors for Bidirectional Explanations in Histopathology (2018), in: Lecture Notes in Computer Science, Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2018(8)
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2017
| , Quantitative analysis of medical images: finding relevant regions-of-interest for medical decision support, University of Geneva, 2017 |
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