| EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case N Díaz-Rodríguez, A Lamas, J Sanchez, G Franchi, I Donadello, S Tabik, ... Information Fusion 79, 58-83, 2022 | 85 | 2022 |
| Deep morphological networks G Franchi, A Fehri, A Yao Pattern Recognition 102, 107246, 2020 | 82 | 2020 |
| TRADI: Tracking deep neural network weight distributions G Franchi, A Bursuc, E Aldea, S Dubuisson, I Bloch Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 52 | 2020 |
| Greybox XAI: A Neural-Symbolic learning framework to produce interpretable predictions for image classification A Bennetot, G Franchi, J Del Ser, R Chatila, N Diaz-Rodriguez Knowledge-Based Systems 258, 109947, 2022 | 29 | 2022 |
| Encoding the latent posterior of bayesian neural networks for uncertainty quantification G Franchi, A Bursuc, E Aldea, S Dubuisson, I Bloch IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 27 | 2023 |
| One versus all for deep neural network for uncertainty (ovnni) quantification G Franchi, A Bursuc, E Aldea, S Dubuisson, I Bloch IEEE Access 10, 7300-7312, 2021 | 27 | 2021 |
| Muad: Multiple uncertainties for autonomous driving, a benchmark for multiple uncertainty types and tasks G Franchi, X Yu, A Bursuc, A Tena, R Kazmierczak, S Dubuisson, E Aldea, ... arXiv preprint arXiv:2203.01437, 2022 | 24 | 2022 |
| Morphological principal component analysis for hyperspectral image analysis G Franchi, J Angulo ISPRS International Journal of Geo-Information 5 (6), 83, 2016 | 20 | 2016 |
| Learning deep morphological networks with neural architecture search Y Hu, N Belkhir, J Angulo, A Yao, G Franchi Pattern Recognition 131, 108893, 2022 | 19 | 2022 |
| Latent discriminant deterministic uncertainty G Franchi, X Yu, A Bursuc, E Aldea, S Dubuisson, D Filliat European Conference on Computer Vision, 243-260, 2022 | 17 | 2022 |
| Robust Semantic Segmentation with Superpixel-Mix G Franchi, N Belkhir, ML Ha, Y Hu, A Bursuc, V Blanz, A Yao arXiv preprint arXiv:2108.00968v2, 2021 | 17 | 2021 |
| Packed-ensembles for efficient uncertainty estimation O Laurent, A Lafage, E Tartaglione, G Daniel, JM Martinez, A Bursuc, ... arXiv preprint arXiv:2210.09184, 2022 | 16 | 2022 |
| Enhanced EDX images by fusion of multimodal SEM images using pansharpening techniques G Franchi, J Angulo, M Moreaud, L Sorbier Journal of microscopy 269 (1), 94-112, 2018 | 13 | 2018 |
| Ordering on the probability simplex of endmembers for hyperspectral morphological image processing G Franchi, J Angulo Mathematical Morphology and Its Applications to Signal and Image Processing …, 2015 | 12 | 2015 |
| Slurp: Side learning uncertainty for regression problems X Yu, G Franchi, E Aldea arXiv preprint arXiv:2110.11182, 2021 | 11 | 2021 |
| Bagging stochastic watershed on natural color image segmentation G Franchi, J Angulo Mathematical Morphology and Its Applications to Signal and Image Processing …, 2015 | 10 | 2015 |
| Comparative study on morphological principal component analysis of hyperspectral images G Franchi, J Angulo 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in …, 2014 | 10 | 2014 |
| Hyperspectral image classification with support vector machines on kernel distribution embeddings G Franchi, J Angulo, D Sejdinović 2016 IEEE International conference on image processing (ICIP), 1898-1902, 2016 | 9 | 2016 |
| Scaling for training time and post-hoc out-of-distribution detection enhancement K Xu, R Chen, G Franchi, A Yao arXiv preprint arXiv:2310.00227, 2023 | 8 | 2023 |
| A study of deep perceptual metrics for image quality assessment R Kazmierczak, G Franchi, N Belkhir, A Manzanera, D Filliat arXiv preprint arXiv:2202.08692, 2022 | 7 | 2022 |
Andrei Bursucvaleo.aiVerified email at valeo.com
