| Grab, pay, and eat: Semantic food detection for smart restaurants E Aguilar, B Remeseiro, M Bolaños, P Radeva IEEE Transactions on Multimedia 20 (12), 3266-3275, 2018 | 148 | 2018 |
| Food recognition using fusion of classifiers based on CNNs E Aguilar, M Bolaños, P Radeva Image Analysis and Processing-ICIAP 2017: 19th International Conference …, 2017 | 78 | 2017 |
| Regularized uncertainty-based multi-task learning model for food analysis E Aguilar, M Bolaños, P Radeva Journal of Visual Communication and Image Representation 60, 360-370, 2019 | 62 | 2019 |
| Multiple wavelet pooling for CNNs A Ferrà, E Aguilar, P Radeva Proceedings of the European conference on computer vision (ECCV) workshops, 0-0, 2018 | 25 | 2018 |
| Bayesian deep learning for semantic segmentation of food images E Aguilar, B Nagarajan, B Remeseiro, P Radeva Computers and Electrical Engineering 103, 108380, 2022 | 21 | 2022 |
| Exploring food detection using CNNs E Aguilar, M Bolaños, P Radeva Computer Aided Systems Theory–EUROCAST 2017: 16th International Conference …, 2018 | 20 | 2018 |
| Uncertainty modeling and deep learning applied to food image analysis E Aguilar, B Nagarajan, R Khatun, M Bolaños, P Radeva International Joint Conference on Biomedical Engineering Systems and …, 2020 | 13 | 2020 |
| Uncertainty-aware integration of local and flat classifiers for food recognition E Aguilar, P Radeva Pattern Recognition Letters 136, 237-243, 2020 | 12 | 2020 |
| Continual evidential deep learning for out-of-distribution detection E Aguilar, B Raducanu, P Radeva, J Van de Weijer Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 11 | 2023 |
| Uncertainty-aware data augmentation for food recognition E Aguilar, B Nagarajan, R Khantun, M Bolaños, P Radeva 2020 25th International Conference on Pattern Recognition (ICPR), 4017-4024, 2021 | 11 | 2021 |
| Bayesian DivideMix++ for enhanced learning with noisy labels B Nagarajan, R Marques, E Aguilar, P Radeva Neural Networks 172, 106122, 2024 | 10 | 2024 |
| Uncertainty-aware selecting for an ensemble of deep food recognition models E Aguilar, B Nagarajan, P Radeva Computers in Biology and Medicine 146, 105645, 2022 | 10 | 2022 |
| Nutritional monitoring in older people prevention services B Nagarajan, R Khatun, M Bolaños, E Aguilar, L Angelini, M El Kamali, ... Digital Health Technology for Better Aging: a multidisciplinary approach, 77-102, 2021 | 8 | 2021 |
| Food recognition by integrating local and flat classifiers E Aguilar, P Radeva Iberian Conference on Pattern Recognition and Image Analysis, 65-74, 2019 | 7 | 2019 |
| Class-conditional data augmentation applied to image classification E Aguilar, P Radeva Computer Analysis of Images and Patterns: 18th International Conference …, 2019 | 7 | 2019 |
| Robust Deep Neural Network for Learning in Noisy Multi-Label Food Images R Morales, A Martinez-Arroyo, E Aguilar Sensors 24 (7), 2034, 2024 | 4 | 2024 |
| Exploring multi-food detection using deep learning-based algorithms R Morales, J Quispe, E Aguilar 2023 IEEE 13th International Conference on Pattern Recognition Systems …, 2023 | 4 | 2023 |
| S2ML-TL framework for multi-label food recognition B Nagarajan, E Aguilar, P Radeva International Conference on Pattern Recognition, 629-646, 2021 | 4 | 2021 |
| Deep ensemble-based hard sample mining for food recognition B Nagarajan, M Bolaños, E Aguilar, P Radeva Journal of Visual Communication and Image Representation 95, 103905, 2023 | 3 | 2023 |
| Can deep learning models recognize chilean diet B Muñoz, I Chirino, E Aguilar IEEE Latin America Transactions 20 (9), 2131-2138, 2022 | 2 | 2022 |
petia radevaFull professor, University of BarcelonaCorreu electrònic verificat a ub.edu
