MDLTREM 2023: Recent Advances of Machine Learning and Deep Learning Techniques for Remote Elderly Monitoring
Recent advances in Machine Learning (ML) and Deep Learning (DL) have led to remarkable results in many fields such as pattern recognition, and machine vision. There have been a great challenges in using machine learning and deep learning methods, combined with other vision techniques to develop autonomous systems that can solve vision problems in different fields.
This Special Session on Recent Advances of Machine Learning and Deep Learning for Elderly people Remote Monitoring system (MDLTREM 2023) at the 17th International Symposium on Innovations in Intelligent SysTems and Applications 2023 (INISTA 2023) aims to bring together the recent researches, innovative and state-of-the art algorithms and architectures for real time applications in the areas of computer vision, neural networks, image processing, intelligent interfaces, biometrics, and object-vision recognition.
The objective of this session is to integrate the researchers who are working on the application of Machine Learning and Deep Learning Methods in Elderly remote monitoring systems to bring the evolution and the benefits of this technology to society.
Submissions offering proof of original applications representing original applications are encouraged novel methodological contributions.
The scope of the MDLTREM 2023 includes, but is not limited to, the following topics:
- Convolutional Neural Networks, Recurrent Neural Networks, Deep Reinforcement Learning methods
- Human-Machine Interface and Integration
- Biomedical Systems, Applications in Medicine
- Object Tracking algorithms
- Signal Processing Techniques and Tools
- Information Processing and Computational Applications
- Image and video processing Techniques
- Posture and Gesture analysis and recognition
- Biometric Features extraction and recognition (face, gait, iris, …)
- Surveillance systems
- …
- Submission of papers: June 15th, 2023
- Notification of acceptance:
July 1st, 2023July 20th, 2023 - Camera-ready papers:
July 10th, 2023July 30th, 2023 - Registration & payment:
July 10th, 2023July 30th, 2023 - Conference date: September 20-23, 2023
All contributions should be original and not published elsewhere or intended to be published during the review period. Authors are invited to submit their papers electronically in pdf format, through EasyChair. Therefore, to submit a paper please activate the following link and select the track: MDLTREM 2023: Recent Advances of Machine Learning and Deep Learning Techniques for Remote Elderly Monitoring
https://easychair.org/conferences/?conf=inista2023
Papers have a maximum page limit of 6 pages including references and graphs. INISTA will offer the option to buy a limited number of extra pages for submission (there will be a charge of 100 euros per extra page). All papers will be thoroughly reviewed by the MDLTREM 2023 Program Committee. All accepted papers must be presented by one of the authors who must register for the conference and pay the fees. Papers included in the proceedings will be submitted to IEEE Xplore only if the paper will be presented at the symposium by one of the authors.
Olfa Jemai
Higher Institute of Computer Sciences and Multimedia of Gabes
Research Team in Intelligent Machine
University of Gabes, Tunisia
E-mail: [email protected]
Ridha Ejbali
Faculty of Sciences of Gabes
Research Team in Intelligent Machine
University of Gabes, Tunisia
E-mail: [email protected]
- Mourad Zaied, University of Gabes, Tunisia
- Salma Jamoussi, University of Sfax, Tunisia
- Ikram Bououd, Kedge business school marseille , France
- Salwa Said, University of Gabes, Tunisia
- Tahani Bouchrika, University of Gabes, Tunisia
- Nedra Beletaief, University of Gabes, Tunisia
- Ines Njeh, University of Gabes, Tunisia
- Hela Lajmi, University of Gabes, Tunisia
- Hela Ltifi, University of Kairouan, Tunisia
- Lotfi Tlig, University of Gabes, Tunisia
- Hasna Njeh, University of Gabes, Tunisia
- Mohamedade Farouk Nanne, Université de Nouakchott Al-Asriya, Mauritanie
- Cheikh Ahmadou Bamba GUEYE, Université Cheikh Anta Diop de Dakar, Sénégal
- Hala Bezine, University of Sfax, Tunisia
