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| Bcn20000: Dermoscopic lesions in the wild M Combalia, NCF Codella, V Rotemberg, B Helba, V Vilaplana, O Reiter, ... arXiv preprint arXiv:1908.02288, 2019 | 790 | 2019 |
| Standardized assessment of automatic segmentation of white matter hyperintensities and results of the WMH segmentation challenge HJ Kuijf, JM Biesbroek, J De Bresser, R Heinen, S Andermatt, M Bento, ... IEEE transactions on medical imaging 38 (11), 2556-2568, 2019 | 411 | 2019 |
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| Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry J Gené-Mola, R Sanz-Cortiella, JR Rosell-Polo, JR Morros, ... Computers and Electronics in Agriculture 169, 105165, 2020 | 214 | 2020 |
| Multi-modal deep learning for Fuji apple detection using RGB-D cameras and their radiometric capabilities J Gené-Mola, V Vilaplana, JR Rosell-Polo, JR Morros, J Ruiz-Hidalgo, ... Computers and Electronics in Agriculture 162, 689-698, 2019 | 196 | 2019 |
| Binary partition trees for object detection V Vilaplana, F Marques, P Salembier IEEE Transactions on Image Processing 17 (11), 2201-2216, 2008 | 153 | 2008 |
| Fruit detection in an apple orchard using a mobile terrestrial laser scanner J Gené-Mola, E Gregorio, J Guevara, F Auat, R Sanz-Cortiella, A Escolà, ... Biosystems engineering 187, 171-184, 2019 | 147 | 2019 |
| Brain MRI super-resolution using 3D generative adversarial networks I Sánchez, V Vilaplana First International Conference on Medical Imaging with Deep Learning, MIDL 2018, 2018 | 146 | 2018 |
| Super-resolution of sentinel-2 imagery using generative adversarial networks L Salgueiro Romero, J Marcello, V Vilaplana Remote Sensing 12 (15), 2424, 2020 | 130 | 2020 |
| Bcn20000: Dermoscopic lesions in the wild C Hernández-Pérez, M Combalia, S Podlipnik, NCF Codella, ... Scientific data 11 (1), 641, 2024 | 106 | 2024 |
| Uncertainty estimation in deep neural networks for dermoscopic image classification M Combalia, F Hueto, S Puig, J Malvehy, V Vilaplana Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 102 | 2020 |
| QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation-analysis of ranking scores and benchmarking results R Mehta, A Filos, U Baid, C Sako, R McKinley, M Rebsamen, K Dätwyler, ... The journal of machine learning for biomedical imaging 2022, https://www …, 2022 | 88 | 2022 |
| MRI Brain Tumor Segmentation and Uncertainty Estimation Using 3D-UNet Architectures L Mora, V Vilaplana BrainLes2020. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic …, 2021 | 69* | 2021 |
| Cascaded V-Net Using ROI Masks for Brain Tumor Segmentation A Casamitjana, M Catà, I Sánchez, M Combalia, V Vilaplana International MICCAI Brainlesion Workshop, 381-391, 2017 | 68 | 2017 |
| 3D Convolutional Neural Networks for Brain Tumor Segmentation: a comparison of multi-resolution architectures A Casamitjana, S Puch, A Aduriz, V Vilaplana International Workshop on Brainlesion: Glioma, Multiple Sclerosis, Stroke …, 2016 | 67 | 2016 |
| Looking behind occlusions: A study on amodal segmentation for robust on-tree apple fruit size estimation J Gené-Mola, M Ferrer-Ferrer, E Gregorio, PM Blok, J Hemming, ... Computers and Electronics in Agriculture 209, 107854, 2023 | 66 | 2023 |
| Leishmaniasis parasite segmentation and classification using deep learning M Górriz, A Aparicio, B Raventós, V Vilaplana, E Sayrol, D López-Codina International Conference on Articulated Motion and Deformable Objects, 53-62, 2018 | 66 | 2018 |
| Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration … I Cumplido-Mayoral, M García-Prat, G Operto, C Falcon, M Shekari, ... Elife 12, e81067, 2023 | 61 | 2023 |
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Josep Ramon MorrosUniversitat Politècnica de Catalunya (UPC)Verified email at upc.edu
