| Skin lesion synthesis with generative adversarial networks A Bissoto, F Perez, E Valle, S Avila OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy …, 2018 | 136 | 2018 |
| Gan-based data augmentation and anonymization for skin-lesion analysis: A critical review A Bissoto, E Valle, S Avila Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 102 | 2021 |
| A survey on deep learning for skin lesion segmentation Z Mirikharaji, K Abhishek, A Bissoto, C Barata, S Avila, E Valle, ME Celebi, ... Medical Image Analysis 88, 102863, 2023 | 96 | 2023 |
| Debiasing skin lesion datasets and models? not so fast A Bissoto, E Valle, S Avila Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 68 | 2020 |
| Deep-learning ensembles for skin-lesion segmentation, analysis, classification: RECOD titans at ISIC challenge 2018 A Bissoto, F Perez, V Ribeiro, M Fornaciali, S Avila, E Valle arXiv preprint arXiv:1808.08480, 2018 | 55 | 2018 |
| (De) Constructing bias on skin lesion datasets A Bissoto, M Fornaciali, E Valle, S Avila Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 50* | 2019 |
| An evaluation of self-supervised pre-training for skin-lesion analysis L Chaves, A Bissoto, E Valle, S Avila European Conference on Computer Vision, 150-166, 2022 | 23 | 2022 |
| The six fronts of the generative adversarial networks A Bissoto, E Valle, S Avila arXiv preprint arXiv:1910.13076, 2019 | 21 | 2019 |
| Artifact-based domain generalization of skin lesion models A Bissoto, C Barata, E Valle, S Avila European Conference on Computer Vision, 133-149, 2022 | 17 | 2022 |
| Even small correlation and diversity shifts pose dataset-bias issues A Bissoto, C Barata, E Valle, S Avila Pattern Recognition Letters 179, 87-93, 2024 | 5 | 2024 |
| The Performance of Transferability Metrics Does Not Translate to Medical Tasks L Chaves, A Bissoto, E Valle, S Avila MICCAI Workshop on Domain Adaptation and Representation Transfer, 105-114, 2023 | 5 | 2023 |
| Global and local explanations for skin cancer diagnosis using prototypes C Santiago, M Correia, MR Verdelho, A Bissoto, C Barata International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 4 | 2023 |
| Improving Skin Lesion Analysis with Generative Adversarial Networks A Bissoto, S Avila Anais Estendidos do XXXIII conference on graphics, patterns and images, 70-76, 2020 | 4 | 2020 |
| BiasPruner: Debiased Continual Learning for Medical Image Classification N Bayasi, J Fayyad, A Bissoto, G Hamarneh, R Garbi International Conference on Medical Image Computing and Computer-Assisted …, 2024 | 3 | 2024 |
| Test-Time Selection for Robust Skin Lesion Analysis A Bissoto, C Barata, E Valle, S Avila International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 3 | 2023 |
| MMIST-ccRCC: A Real World Medical Dataset for the Development of Multi-Modal Systems T Mota, MR Verdelho, DJ Araújo, A Bissoto, C Santiago, C Barata Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 2 | 2024 |
| Generating high quality synthetic skin lesions for boosting automated screening A Bissoto, M Fornaciali, E Valle, S Avila International Educational Symposium of the Melanoma World Society, 43-43, 2018 | 2 | 2018 |
| Are Explanations Helpful? A Comparative Analysis of Explainability Methods in Skin Lesion Classifiers RYG Paccotacya-Yanque, A Bissoto, S Avila 2024 20th International Symposium on Medical Information Processing and …, 2024 | 1 | 2024 |
| XAI for Skin Cancer Detection with Prototypes and Non-Expert Supervision M Correia, A Bissoto, C Santiago, C Barata arXiv preprint arXiv:2402.01410, 2024 | 1 | 2024 |
| Key Patches Are All You Need: A Multiple Instance Learning Framework For Robust Medical Diagnosis DJ Araújo, MR Verdelho, A Bissoto, JC Nascimento, C Santiago, C Barata Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
Sandra AvilaProfessor of Computer Science, University of Campinas (Unicamp)Подтвержден адрес электронной почты в домене ic.unicamp.br