no code implementations • 31 Jan 2024 • Layth Hamad, Muhammad Asif Khan, Hamid Menouar, Fethi Filali, Amr Mohamed
This paper presents Haris, an advanced autonomous mobile robot system for tracking the location of vehicles in crowded car parks using license plate recognition.
no code implementations • 11 Jan 2024 • Amr Mohamed, Mahmoud Rabea, Aya Sameh, Ehab Kamal
The RSNA-MICCAI brain tumor radiogenomic classification challenge aimed to predict MGMT biomarker status in glioblastoma through binary classification on Multi parameter mpMRI scans: T1w, T1wCE, T2w and FLAIR.
no code implementations • 8 Oct 2023 • Abdulrahman Soliman, Amr Mohamed, Elias Yaacoub, Nikhil V. Navkar, Aiman Erbad
Telemedicine applications have recently received substantial potential and interest, especially after the COVID-19 pandemic.
no code implementations • 21 Jul 2023 • Emna Baccour, Mhd Saria Allahham, Aiman Erbad, Amr Mohamed, Ahmed Refaey Hussein, Mounir Hamdi
In this context, we introduce a novel platform architecture to deploy a zero-touch PAI-as-a-Service (PAIaaS) in 6G networks supported by a blockchain-based smart system.
no code implementations • 27 Aug 2022 • Emna Baccour, Aiman Erbad, Amr Mohamed, Mounir Hamdi, Mohsen Guizani
In this paper, we present an approach that targets the security of collaborative deep inference via re-thinking the distribution strategy, without sacrificing the model performance.
no code implementations • 25 Sep 2021 • Mhd Saria Allahham, Sameh Sorour, Amr Mohamed, Aiman Erbad, Mohsen Guizani
Therefore, it is crucial to motivate edge devices to become learners and offer their computing resources, and either offer their private data or receive the needed data from the orchestrator and participate in the training process of a learning task.
no code implementations • 2 Sep 2021 • Mhd Saria Allahham, Sameh Sorour, Amr Mohamed, Aiman Erbad, Mohsen Guizani
The heterogeneity in edge devices' capabilities will require the joint optimization of the learners-orchestrator association and task allocation.
no code implementations • 5 Aug 2021 • Alaa Awad Abdellatif, Naram Mhaisen, Zina Chkirbene, Amr Mohamed, Aiman Erbad, Mohsen Guizani
After that, we provide a deep literature review for the applications of RL in I-health systems.
1 code implementation • 19 Jul 2021 • Dawei Du, Longyin Wen, Pengfei Zhu, Heng Fan, QinGhua Hu, Haibin Ling, Mubarak Shah, Junwen Pan, Ali Al-Ali, Amr Mohamed, Bakour Imene, Bin Dong, Binyu Zhang, Bouchali Hadia Nesma, Chenfeng Xu, Chenzhen Duan, Ciro Castiello, Corrado Mencar, Dingkang Liang, Florian Krüger, Gennaro Vessio, Giovanna Castellano, Jieru Wang, Junyu Gao, Khalid Abualsaud, Laihui Ding, Lei Zhao, Marco Cianciotta, Muhammad Saqib, Noor Almaadeed, Omar Elharrouss, Pei Lyu, Qi Wang, Shidong Liu, Shuang Qiu, Siyang Pan, Somaya Al-Maadeed, Sultan Daud Khan, Tamer Khattab, Tao Han, Thomas Golda, Wei Xu, Xiang Bai, Xiaoqing Xu, Xuelong Li, Yanyun Zhao, Ye Tian, Yingnan Lin, Yongchao Xu, Yuehan Yao, Zhenyu Xu, Zhijian Zhao, Zhipeng Luo, Zhiwei Wei, Zhiyuan Zhao
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.
1 code implementation • 14 Jul 2021 • Alaa Awad Abdellatif, Naram Mhaisen, Amr Mohamed, Aiman Erbad, Mohsen Guizani, Zaher Dawy, Wassim Nasreddine
Federated learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data.
no code implementations • 4 Jun 2021 • Emna Baccour, Fatima Haouari, Aiman Erbad, Amr Mohamed, Kashif Bilal, Mohsen Guizani, Mounir Hamdi
Crowdsourced live video streaming (livecast) services such as Facebook Live, YouNow, Douyu and Twitch are gaining more momentum recently.
no code implementations • 23 May 2021 • Mohammed Jouhari, Abdulla Al-Ali, Emna Baccour, Amr Mohamed, Aiman Erbad, Mohsen Guizani, Mounir Hamdi
Unmanned Aerial Vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems relying on direct observations obtained from fixed cameras and sensors.
no code implementations • 4 May 2021 • Emna Baccour, Naram Mhaisen, Alaa Awad Abdellatif, Aiman Erbad, Amr Mohamed, Mounir Hamdi, Mohsen Guizani
The confluence of pervasive computing and artificial intelligence, Pervasive AI, expanded the role of ubiquitous IoT systems from mainly data collection to executing distributed computations with a promising alternative to centralized learning, presenting various challenges.
no code implementations • 31 Mar 2021 • Ali Hamdi, Khaled Shaban, Abdelkarim Erradi, Amr Mohamed, Shakila Khan Rumi, Flora Salim
Specifically, we investigate the challenging issues in regards to spatiotemporal relationships, interdisciplinarity, discretisation, and data characteristics.
no code implementations • 10 Dec 2020 • Naram Mhaisen, Alaa Awad, Amr Mohamed, Aiman Erbad, Mohsen Guizani
Distributed learning algorithms aim to leverage distributed and diverse data stored at users' devices to learn a global phenomena by performing training amongst participating devices and periodically aggregating their local models' parameters into a global model.
no code implementations • 27 Jun 2020 • Alaa Awad Abdellatif, Lutfi Samara, Amr Mohamed, Mohsen Guizani, Aiman Erbad, Abdulla Al-Ali
Rapid evolution of wireless medical devices and network technologies has fostered the growth of remote monitoring systems.
no code implementations • 20 Jun 2019 • Fatima Haouari, Emna Baccour, Aiman Erbad, Amr Mohamed, Mohsen Guizani
This can be achieved by advocating a geo-distributed cloud infrastructure to allocate the multimedia resources as close as possible to viewers, in order to minimize the access delay and video stalls.
no code implementations • 23 Oct 2018 • Reza Shakeri, Mohammed Ali Al-Garadi, Ahmed Badawy, Amr Mohamed, Tamer Khattab, Abdulla Al-Ali, Khaled A. Harras, Mohsen Guizani
We present and propose state-of-the-art algorithms to address design challenges with both quantitative and qualitative methods and map these challenges with important CPS applications to draw insightful conclusions on the challenges of each application.
no code implementations • 29 Jul 2018 • Mohammed Ali Al-Garadi, Amr Mohamed, Abdulla Al-Ali, Xiaojiang Du, Mohsen Guizani
Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems.
no code implementations • 27 Mar 2017 • Ahmed Ben Said, Amr Mohamed, Tarek Elfouly, Khaled Harras, Z. Jane Wang
In this paper, we present a joint compression and classification approach of EEG and EMG signals using a deep learning approach.
no code implementations • 30 Mar 2014 • Ahmed El Shafie, Tamer Khattab, Hussien Saad, Amr Mohamed
It manages the flow of the undelivered primary packets to its relaying queue using the appropriate actions over time slots.