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ORCIDAlice Othmani
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2020 – today
- 2024
[j22]Yahaya Idris Abubakar
, Alice Othmani, Patrick Siarry, Aznul Qalid Md Sabri:
A Systematic Review of Rare Events Detection Across Modalities Using Machine Learning and Deep Learning. IEEE Access 12: 47091-47109 (2024)- [j21]Yun Xin Teoh, Alice Othmani, Siew-Li Goh, Juliana Usman, Khin Wee Lai:
Deciphering Knee Osteoarthritis Diagnostic Features With Explainable Artificial Intelligence: A Systematic Review. IEEE Access 12: 109080-109108 (2024) - [j20]Mamadou Dia, Ghazaleh Khodabandelou, Aznul Qalid Md Sabri, Alice Othmani:
Video-based continuous affect recognition of children with Autism Spectrum Disorder using deep learning. Biomed. Signal Process. Control. 89: 105712 (2024) - [j19]Mamadou Dia, Ghazaleh Khodabandelou, Alice Othmani:
Paying attention to uncertainty: A stochastic multimodal transformers for post-traumatic stress disorder detection using video. Comput. Methods Programs Biomed. 257: 108439 (2024) - [j18]Moctar Abdoul Latif Sawadogo, Furkan Pala, Gurkirat Singh, Imen Selmi, Pauline Puteaux, Alice Othmani:
PTSD in the wild: a video database for studying post-traumatic stress disorder recognition in unconstrained environments. Multim. Tools Appl. 83(14): 42861-42883 (2024) - [j17]Stephen Khor Wen Hwooi, Aznul Qalid Md Sabri, Alice Othmani:
Autism classification and monitoring from predicted categorical and dimensional emotions of video features. Signal Image Video Process. 18(1): 191-198 (2024) - [c14]Amine Lagzouli, Peter Pivonka, David Cooper, Vittorio Sansalone, Alice Othmani:
Dbahnet: Dual-Branch Attention-Based Hybrid Network for High-Resolution 3d Micro-Ct Bone Scan Segmentation. ISBI 2024: 1-5 - [i14]Yun Xin Teoh, Alice Othmani, Siew-Li Goh, Juliana Usman, Khin Wee Lai:
Segmentation of Knee Bones for Osteoarthritis Assessment: A Comparative Analysis of Supervised, Few-Shot, and Zero-Shot Learning Approaches. CoRR abs/2403.08761 (2024) - [i13]Mamadou Dia, Ghazaleh Khodabandelou, Alice Othmani:
A Novel Stochastic Transformer-based Approach for Post-Traumatic Stress Disorder Detection using Audio Recording of Clinical Interviews. CoRR abs/2403.19441 (2024) - 2023
- [j16]Sana Yasin, Alice Othmani, Imran Raza, Syed Asad Hussain:
Machine learning based approaches for clinical and non-clinical depression recognition and depression relapse prediction using audiovisual and EEG modalities: A comprehensive review. Comput. Biol. Medicine 159: 106741 (2023) - [j15]Yun Xin Teoh, Alice Othmani, Khin Wee Lai, Siew-Li Goh, Juliana Usman:
Stratifying knee osteoarthritis features through multitask deep hybrid learning: Data from the osteoarthritis initiative. Comput. Methods Programs Biomed. 242: 107807 (2023) - [j14]Alice Othmani, Aznul Qalid Md Sabri, Sinem Aslan, Faten Chaieb, Hala Rameh, Romain Alfred, Dayron Cohen:
EEG-based neural networks approaches for fatigue and drowsiness detection: A survey. Neurocomputing 557: 126709 (2023) - [j13]Alice Othmani, Duqing Han, Xin Gao, Runpeng Ye, Abdenour Hadid:
Kinship recognition from faces using deep learning with imbalanced data. Multim. Tools Appl. 82(10): 15859-15874 (2023) - [c13]Yun Xin Teoh, Alice Othmani, Siew-Li Goh, Juliana Usman, Khin Wee Lai:
Predicting Knee Osteoarthritis Pain Severity through A Deep Hybrid Learning Model: Data from the Osteoarthritis Initiative. BIBM 2023: 4148-4153 - [c12]Mustaqeem Khan, Ufaq Khan, Alice Othmani:
PD-Net: Multi-Stream Hybrid Healthcare System for Parkinson's Disease Detection using Multi Learning Trick Approach. CBMS 2023: 382-385 - [c11]Mamadou Dia, Ghazaleh Khodabandelou, Alice Othmani:
A Novel Stochastic Transformer-based Approach for Post-Traumatic Stress Disorder Detection using Audio Recording of Clinical Interviews. CBMS 2023: 700-705 - [c10]Hacene Terbouche, Maryan Morel, Mariano Rodriguez, Alice Othmani:
Multi-Annotation Attention Model for Video Summarization. CVPR Workshops 2023: 3143-3152 - [c9]Stephen Khor Wen Hwooi, Alice Othmani, Aznul Qalid Md Sabri:
Monitoring Application-driven Continuous Affect Recognition From Video Frames. IVSP 2023: 36-42 - [c8]Alice Othmani, Muhammad Muzammel:
An Ambient Intelligence-Based Approach for Longitudinal Monitoring of Verbal and Vocal Depression Symptoms. PRIME@MICCAI 2023: 206-217 - [i12]Alice Othmani, Muhammad Muzammel:
An Ambient Intelligence-based Approach For Longitudinal Monitoring of Verbal and Vocal Depression Symptoms. CoRR abs/2308.08472 (2023) - [i11]Yun Xin Teoh, Alice Othmani, Siew-Li Goh, Juliana Usman, Khin Wee Lai:
Deciphering knee osteoarthritis diagnostic features with explainable artificial intelligence: A systematic review. CoRR abs/2308.09380 (2023) - 2022
- [j12]Hacene Terbouche, Liam Schoneveld, Oisin Benson, Alice Othmani:
Comparing Learning Methodologies for Self-Supervised Audio-Visual Representation Learning. IEEE Access 10: 41622-41638 (2022) - [j11]Stephen Khor Wen Hwooi, Alice Othmani, Aznul Qalid Md Sabri:
Deep Learning-Based Approach for Continuous Affect Prediction From Facial Expression Images in Valence-Arousal Space. IEEE Access 10: 96053-96065 (2022) - [j10]Emna Rejaibi, Ali Komaty, Fabrice Mériaudeau, Said Agrebi, Alice Othmani:
MFCC-based Recurrent Neural Network for automatic clinical depression recognition and assessment from speech. Biomed. Signal Process. Control. 71(Part): 103107 (2022) - [j9]Alice Othmani, Assaad Oussama Zeghina, Muhammad Muzammel:
A Model of Normality Inspired Deep Learning Framework for Depression Relapse Prediction Using Audiovisual Data. Comput. Methods Programs Biomed. 226: 107132 (2022) - [c7]Ahana Bandyopadhyay, Sourodip Ghosh, Moinak Bose, Arun Singh, Alice Othmani, KC Santosh:
Alzheimer's Disease Detection Using Ensemble Learning and Artificial Neural Networks. RTIP2R 2022: 12-21 - [c6]Alice Othmani, Thibaut Bizet, Tanguy Pellerin, Badr Hamdi, Marc-Antoine Bock, Soumyabrata Dev:
Significant CC400 Functional Brain Parcellations Based LeNet5 Convolutional Neural Network for Autism Spectrum Disorder Detection. RTIP2R 2022: 34-45 - [i10]Liam Schoneveld, Alice Othmani:
Towards a General Deep Feature Extractor for Facial Expression Recognition. CoRR abs/2201.07781 (2022) - [i9]Moctar Abdoul Latif Sawadogo, Furkan Pala, Gurkirat Singh, Imen Selmi, Pauline Puteaux, Alice Othmani:
PTSD in the Wild: A Video Database for Studying Post-Traumatic Stress Disorder Recognition in Unconstrained Environments. CoRR abs/2209.14085 (2022) - [i8]Jason Walsh, Alice Othmani, Mayank Jain, Soumyabrata Dev:
Using U-Net Network for Efficient Brain Tumor Segmentation in MRI Images. CoRR abs/2211.01885 (2022) - 2021
- [j8]Sana Yasin, Syed Asad Hussain, Sinem Aslan, Imran Raza, Muhammad Muzammel, Alice Othmani:
EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review. Comput. Methods Programs Biomed. 202: 106007 (2021) - [j7]Muhammad Muzammel, Hanan Salam, Alice Othmani:
End-to-end multimodal clinical depression recognition using deep neural networks: A comparative analysis. Comput. Methods Programs Biomed. 211: 106433 (2021) - [j6]Ahmed Rachid Hazourli, Amine Djeghri, Hanan Salam, Alice Othmani:
Multi-facial patches aggregation network for facial expression recognition and facial regions contributions to emotion display. Multim. Tools Appl. 80(9): 13639-13662 (2021) - [j5]Liam Schoneveld, Alice Othmani, Hazem Abdelkawy:
Leveraging recent advances in deep learning for audio-Visual emotion recognition. Pattern Recognit. Lett. 146: 1-7 (2021) - [c5]Muhammad Muzammel, Alice Othmani, Himadri Mukherjee, Hanan Salam:
Identification of Signs of Depression Relapse using Audio-visual Cues: A Preliminary Study. CBMS 2021: 62-67 - [c4]Himadri Mukherjee, Hanan Salam, Alice Othmani, KC Santosh:
How Intense Are Your Words? Understanding Emotion Intensity from Speech. ICCT 2021: 1280-1286 - [c3]Liam Schoneveld, Alice Othmani:
Towards a General Deep Feature Extractor for Facial Expression Recognition. ICIP 2021: 2339-2342 - [i7]Liam Schoneveld, Alice Othmani, Hazem Abdelkawy:
Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition. CoRR abs/2103.09154 (2021) - 2020
- [j4]Alice Othmani, Abdul Rahman Taleb, Hazem Abdelkawy, Abdenour Hadid:
Age estimation from faces using deep learning: A comparative analysis. Comput. Vis. Image Underst. 196: 102961 (2020) - [j3]Remy Kusters, Dusan Misevic, Hugues Berry, Antoine Cully, Yann Le Cunff, Loic Dandoy, Natalia Díaz Rodríguez, Marion Ficher, Jonathan Grizou, Alice Othmani, Themis Palpanas, Matthieu Komorowski, Patrick Loiseau, Clément Moulin-Frier, Santino Nanini, Daniele Quercia, Michèle Sebag, Françoise Fogelman-Soulié, Sofiane Taleb, Liubov Tupikina, Vaibhav Sahu, Jill-Jênn Vie, Fatima Wehbi:
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities. Frontiers Big Data 3: 577974 (2020) - [j2]Muhammad Ilyas, Alice Othmani, Amine Naït-Ali:
Computer-aided prediction of hearing loss based on auditory perception. Multim. Tools Appl. 79(21-22): 15765-15789 (2020) - [j1]Muhammad Ilyas, Alice Othmani, Amine Naït-Ali:
Auditory perception based system for age classification and estimation using dynamic frequency sound. Multim. Tools Appl. 79(29-30): 21603-21626 (2020) - [c2]Alice Othmani, Daoud Kadoch, Kamil Bentounes, Emna Rejaibi, Romain Alfred, Abdenour Hadid:
Towards Robust Deep Neural Networks for Affect and Depression Recognition from Speech. ICPR Workshops (2) 2020: 5-19 - [i6]Ahmed Rachid Hazourli, Amine Djeghri, Hanan Salam, Alice Othmani:
Deep Multi-Facial Patches Aggregation Network For Facial Expression Recognition. CoRR abs/2002.09298 (2020) - [i5]Sana Yasin, Syed Asad Hussain, Sinem Aslan, Imran Raza, Muhammad Muzammel, Alice Othmani:
Neural Networks based approaches for Major Depressive Disorder and Bipolar Disorder Diagnosis using EEG signals: A review. CoRR abs/2009.13402 (2020) - [i4]Muhammad Muzammel, Hanan Salam, Yann Hoffmann, Mohamed Chetouani, Alice Othmani:
AudVowelConsNet: A Phoneme-Level Based Deep CNN Architecture for Clinical Depression Diagnosis. CoRR abs/2010.16201 (2020)
2010 – 2019
- 2019
- [i3]Alice Othmani, Fakhri Torkhani, Jean-Marie Favreau:
3D Geometric salient patterns analysis on 3D meshes. CoRR abs/1906.07645 (2019) - [i2]Emna Rejaibi, Ali Komaty, Fabrice Mériaudeau, Said Agrebi, Alice Othmani:
MFCC-based Recurrent Neural Network for Automatic Clinical Depression Recognition and Assessment from Speech. CoRR abs/1909.07208 (2019) - [i1]Emna Rejaibi, Daoud Kadoch, Kamil Bentounes, Romain Alfred, Mohamed Daoudi, Abdenour Hadid, Alice Othmani:
Clinical Depression and Affect Recognition with EmoAudioNet. CoRR abs/1911.00310 (2019) - 2018
- [c1]Muhammad Ilyas, Alice Othmani, Amine Naït-Ali:
Prediction of Hearing Loss Based on Auditory Perception: A Preliminary Study. PRIME@MICCAI 2018: 34-41
Coauthor Index
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last updated on 2024-10-31 20:18 CET by the dblp team
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