| Yedroudj-net: An efficient CNN for spatial steganalysis M Yedroudj, F Comby, M Chaumont 2018 IEEE international conference on acoustics, speech and signal …, 2018 | 320 | 2018 |
| Camera model identification with the use of deep convolutional neural networks A Tuama, F Comby, M Chaumont 2016 IEEE International workshop on information forensics and security (WIFS …, 2016 | 279 | 2016 |
| Camera model identification based machine learning approach with high order statistics features A Tuama, F Comby, M Chaumont 2016 24th European Signal Processing Conference (EUSIPCO), 1183-1187, 2016 | 55 | 2016 |
| How to augment a small learning set for improving the performances of a CNN-based steganalyzer? M Yedroudj, M Chaumont, F Comby arXiv preprint arXiv:1801.04076, 2018 | 47 | 2018 |
| Steganography using a 3-player game M Yedroudj, F Comby, M Chaumont Journal of Visual Communication and Image Representation 72, 102910, 2020 | 40 | 2020 |
| Fuzzy edge detection for omnidirectional images F Jacquey, F Comby, O Strauss Fuzzy sets and Systems 159 (15), 1991-2010, 2008 | 40 | 2008 |
| Variable structuring element based fuzzy morphological operations for single viewpoint omnidirectional images O Strauss, F Comby Pattern Recognition 40 (12), 3578-3596, 2007 | 39 | 2007 |
| A CNN adapted to time series for the classification of Supernovae A Brunel, J Pasquet, J Pasquet, N Rodriguez, F Comby, D Fouchez, ... arXiv preprint arXiv:1901.00461, 2019 | 37 | 2019 |
| Pixels-off: data-augmentation complementary solution for deep-learning steganalysis M Yedroudj, M Chaumont, F Comby, A Oulad Amara, P Bas Proceedings of the 2020 ACM workshop on information hiding and multimedia …, 2020 | 28 | 2020 |
| Multibeam sonar image matching for terrain-based underwater navigation O Strauss, F Comby, MJ Aldon Oceans' 99. MTS/IEEE. Riding the Crest into the 21st Century. Conference and …, 1999 | 28 | 1999 |
| Rough histograms for robust statistics O Strauss, F Comby, MJ Aldon Proceedings 15th International Conference on Pattern Recognition. ICPR-2000 …, 2000 | 26 | 2000 |
| Non-additive approach for gradient-based edge detection F Jacquey, K Loquin, F Comby, O Strauss 2007 IEEE International Conference on Image Processing 3, III-49-III-52, 2007 | 22 | 2007 |
| Source camera model identification using features from contaminated sensor noise A Tuama, F Comby, M Chaumont Digital-Forensics and Watermarking: 14th International Workshop, IWDW 2015 …, 2016 | 17 | 2016 |
| Fuzzy morphology for omnidirectional images. O Strauss, F Comby ICIP (2), 141-144, 2005 | 17 | 2005 |
| High dynamic range images from digital cameras raw data G Joffre, W Puech, F Comby, J Joffre ACM SIGGRAPH 2005 Posters, 72-es, 2005 | 16 | 2005 |
| Analysis of the scalability of a deep-learning network for steganography “into the wild” H Ruiz, M Chaumont, M Yedroudj, AO Amara, F Comby, G Subsol Pattern Recognition. ICPR International Workshops and Challenges: Virtual …, 2021 | 13 | 2021 |
| Highly specific pose estimation with a catadioptric omnidirectional camera B Magnier, F Comby, O Strauss, J Triboulet, C Demonceaux 2010 IEEE International Conference on Imaging Systems and Techniques, 229-233, 2010 | 12 | 2010 |
| Non-additive imprecise image super-resolution in a semi-blind context F Graba, F Comby, O Strauss IEEE Transactions on Image Processing 26 (3), 1379-1392, 2016 | 10 | 2016 |
| Non-additive approach for omnidirectional image gradient estimation F Jacquey, F Comby, O Strauss 2007 IEEE 11th International Conference on Computer Vision, 1-6, 2007 | 10 | 2007 |
| Using quasi-continuous histograms for fuzzy main motion estimation in video sequence F Comby, O Strauss Fuzzy Sets and Systems 158 (5), 475-495, 2007 | 10 | 2007 |
