| MFCC-based recurrent neural network for automatic clinical depression recognition and assessment from speech E Rejaibi, A Komaty, F Meriaudeau, S Agrebi, A Othmani Biomedical Signal Processing and Control 71, 103107, 2022 | 212 | 2022 |
| Leveraging recent advances in deep learning for audio-visual emotion recognition L Schoneveld, A Othmani, H Abdelkawy Pattern Recognition Letters 146, 1-7, 2021 | 189 | 2021 |
| EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review S Yasin, SA Hussain, S Aslan, I Raza, M Muzammel, A Othmani Computer Methods and Programs in Biomedicine 202, 106007, 2021 | 129 | 2021 |
| Single tree species classification from terrestrial laser scanning data for forest inventory A Othmani, LFCLY Voon, C Stolz, A Piboule Pattern Recognition Letters 34 (16), 2144-2150, 2013 | 87 | 2013 |
| Towards automated and operational forest inventories with T-Lidar A Othmani, A Piboule, M Krebs, C Stolz, LFCLY Voon 11th international conference on LiDAR applications for assessing forest …, 2011 | 80 | 2011 |
| AudVowelConsNet: A phoneme-level based deep CNN architecture for clinical depression diagnosis M Muzammel, H Salam, Y Hoffmann, M Chetouani, A Othmani Machine Learning with Applications 2, 100005, 2020 | 70 | 2020 |
| Age estimation from faces using deep learning: A comparative analysis A Othmani, AR Taleb, H Abdelkawy, A Hadid Computer Vision and Image Understanding 196, 102961, 2020 | 70 | 2020 |
| Interdisciplinary research in artificial intelligence: challenges and opportunities R Kusters, D Misevic, H Berry, A Cully, Y Le Cunff, L Dandoy, ... Frontiers in big data 3, 577974, 2020 | 69 | 2020 |
| Settlement inhibition of marine biofilm bacteria and barnacle larvae by compounds isolated from the Mediterranean brown alga Taonia atomaria A Othmani, R Bunet, JL Bonnefont, JF Briand, G Culioli Journal of Applied Phycology 28, 1975-1986, 2016 | 58 | 2016 |
| End-to-end multimodal clinical depression recognition using deep neural networks: A comparative analysis M Muzammel, H Salam, A Othmani Computer Methods and Programs in Biomedicine 211, 106433, 2021 | 56 | 2021 |
| Using U-Net network for efficient brain tumor segmentation in MRI images J Walsh, A Othmani, M Jain, S Dev Healthcare Analytics 2, 100098, 2022 | 52 | 2022 |
| Towards robust deep neural networks for affect and depression recognition from speech A Othmani, D Kadoch, K Bentounes, E Rejaibi, R Alfred, A Hadid Pattern Recognition. ICPR International Workshops and Challenges: Virtual …, 2021 | 51 | 2021 |
| Active fluctuations of the nuclear envelope shape the transcriptional dynamics in oocytes M Almonacid, A Al Jord, S El-Hayek, A Othmani, F Coulpier, S Lemoine, ... Developmental Cell 51 (2), 145-157. e10, 2019 | 51 | 2019 |
| Temporal covariation of epibacterial community and surface metabolome in the Mediterranean seaweed holobiont Taonia atomaria B Paix, A Othmani, D Debroas, G Culioli, JF Briand Environmental microbiology 21 (9), 3346-3363, 2019 | 48 | 2019 |
| Surface metabolites of the brown alga Taonia atomaria have the ability to regulate epibiosis A Othmani, JF Briand, M Ayé, M Molmeret, G Culioli Biofouling 32 (7), 801-813, 2016 | 41 | 2016 |
| Multi-facial patches aggregation network for facial expression recognition and facial regions contributions to emotion display AR Hazourli, A Djeghri, H Salam, A Othmani Multimedia Tools and Applications 80 (9), 13639-13662, 2021 | 29 | 2021 |
| Artificially decreasing cortical tension generates aneuploidy in mouse oocytes I Bennabi, F Crozet, E Nikalayevich, A Chaigne, G Letort, ... Nature Communications 11 (1), 1649, 2020 | 29 | 2020 |
| A model of normality inspired deep learning framework for depression relapse prediction using audiovisual data A Othmani, AO Zeghina, M Muzammel Computer Methods and Programs in Biomedicine 226, 107132, 2022 | 21 | 2022 |
| Eeg biometrics for person verification B Goudiaby, A Othmani, A Nait-ali Hidden Biometrics: When Biometric Security Meets Biomedical Engineering, 45-69, 2020 | 21 | 2020 |
| Machine learning based approaches for clinical and non-clinical depression recognition and depression relapse prediction using audiovisual and EEG modalities: A comprehensive … S Yasin, A Othmani, I Raza, SA Hussain Computers in Biology and Medicine 159, 106741, 2023 | 20 | 2023 |
nicolas lomenieProfessor of Computer Science, Université Paris Cité在 u-paris.fr 的电子邮件经过验证
