Dr. Abdussalam Elhanashi is a researcher at the Università di Pisa, Italy, specializing in advanced applications of deep learning and video imaging processing. He holds an M.Sc. in Electronics and Electrical Engineering from the University of Glasgow in Scotland and an MBA from the University of Nicosia in Cyprus. He earned his Ph.D. in Information Engineering from the Università di Pisa, funded by a prestigious merit-based scholarship from the Islamic Bank Development (IsDB) as Libya's top candidate in 2019-2020. Dr. Elhanashi was a Research Fellow at the University of Strathclyde in 2021, where he applied deep learning models to analyse CT scans and X-ray images for medical diagnostics. In 2022, he was a visiting researcher at Hiroshima University in Japan, focusing on advanced video analysis techniques. With over 16 years of industry experience, he has successfully managed engineering projects, conducted system maintenance, and performed root cause analyses to address technical challenges. He authored the first Arabic-language book on artificial intelligence in Libya and has contributed to numerous peer-reviewed articles in international conferences and journals. He is a developer at the Society for Imaging Informatics in Medicine (SIIM) in USA. His work focuses on real-world AI applications, lightweight model development, video surveillance, IoT-based low-cost embedded systems, designing AI-driven solutions for medical imaging, and efficient coding techniques for imaging and video processing systems.Sergio Saponara, Director of the Department of Information Engineering at the University of Pisa, IEEE Distinguished Lecturer, obtained his Master's degree cum laude and Ph.D. in Electronic Engineering from the University of Pisa. In 2002, he was a Marie Curie Research Fellow at the Inter-university Microelectronics Center (IMEC) in Leuven, Belgium. He was also a post-graduate researcher at the National Research Council. Currently, he is a Full Professor of Electronics at the University of Pisa, where he teaches courses in Vehicular Electronics, Electronic Systems for Robotics, HW and Embedded Security for the Master's degrees in Vehicle Engineering, Robotics and Automation Engineering, and Cybersecurity. Additionally, he teaches Electronics at the Italian Naval Academy in Livorno. Prof. Saponara was President of the Bachelor's and Master's programs in Electronic Engineering at the University of Pisa. He has co-authored 400 scientific articles indexed in Scopus and 20 patents. He is a Founding Member of the IoT CASS SiG and has been a Program Committee Member for over 100 international IEEE and SPIE conferences. He also serves as the Director of the summer school "Enabling Technologies for the Internet of Things (IoT)" and the specialization course "Automotive Electronics and Powertrain Electrification." He is also the Director of the interUniversity Center for Automotive Research (UCAR).

• 1. Introduction2. Image Analysis for Surveillance: Detecting Fire and Smoke Incidents3. Enhancing COVID-19 Safety Measures with AI-Powered Video Analysis4. Deep Learning Approaches for Fingerprint Image Restoration 4.1 Background5. Deep Learning for Classification and Localization of Multiple Abnormalities on chest x-rays images6. Real-time Stroke Detection Based on Deep Learning and Federated Learning7. Efficient Identification of Bag Breakup in Continuous Airflow via Video Analysis

Dr. Abdussalam Elhanashi is a researcher at the Università di Pisa, Italy, specializing in advanced applications of deep learning and video imaging processing. He holds an M.Sc. in Electronics and Electrical Engineering from the University of Glasgow in Scotland and an MBA from the University of Nicosia in Cyprus. He earned his Ph.D. in Information Engineering from the Università di Pisa, funded by a prestigious merit-based scholarship from the Islamic Bank Development (IsDB) as Libya's top candidate in 2019-2020. Dr. Elhanashi was a Research Fellow at the University of Strathclyde in 2021, where he applied deep learning models to analyse CT scans and X-ray images for medical diagnostics. In 2022, he was a visiting researcher at Hiroshima University in Japan, focusing on advanced video analysis techniques. With over 16 years of industry experience, he has successfully managed engineering projects, conducted system maintenance, and performed root cause analyses to address technical challenges. He authored the first Arabic-language book on artificial intelligence in Libya and has contributed to numerous peer-reviewed articles in international conferences and journals. He is a developer at the Society for Imaging Informatics in Medicine (SIIM) in USA. His work focuses on real-world AI applications, lightweight model development, video surveillance, IoT-based low-cost embedded systems, designing AI-driven solutions for medical imaging, and efficient coding techniques for imaging and video processing systems.Sergio Saponara, Director of the Department of Information Engineering at the University of Pisa, IEEE Distinguished Lecturer, obtained his Master's degree cum laude and Ph.D. in Electronic Engineering from the University of Pisa. In 2002, he was a Marie Curie Research Fellow at the Inter-university Microelectronics Center (IMEC) in Leuven, Belgium. He was also a post-graduate researcher at the National Research Council. Currently, he is a Full Professor of Electronics at the University of Pisa, where he teaches courses in Vehicular Electronics, Electronic Systems for Robotics, HW and Embedded Security for the Master's degrees in Vehicle Engineering, Robotics and Automation Engineering, and Cybersecurity. Additionally, he teaches Electronics at the Italian Naval Academy in Livorno. Prof. Saponara was President of the Bachelor's and Master's programs in Electronic Engineering at the University of Pisa. He has co-authored 400 scientific articles indexed in Scopus and 20 patents. He is a Founding Member of the IoT CASS SiG and has been a Program Committee Member for over 100 international IEEE and SPIE conferences. He also serves as the Director of the summer school "Enabling Technologies for the Internet of Things (IoT)" and the specialization course "Automotive Electronics and Powertrain Electrification." He is also the Director of the interUniversity Center for Automotive Research (UCAR).

• 1. Introduction2. Image Analysis for Surveillance: Detecting Fire and Smoke Incidents3. Enhancing COVID-19 Safety Measures with AI-Powered Video Analysis4. Deep Learning Approaches for Fingerprint Image Restoration 4.1 Background5. Deep Learning for Classification and Localization of Multiple Abnormalities on chest x-rays images6. Real-time Stroke Detection Based on Deep Learning and Federated Learning7. Efficient Identification of Bag Breakup in Continuous Airflow via Video Analysis

Dr. Abdussalam Elhanashi is a researcher at the Università di Pisa, Italy, specializing in advanced applications of deep learning and video imaging processing. He holds an M.Sc. in Electronics and Electrical Engineering from the University of Glasgow in Scotland and an MBA from the University of Nicosia in Cyprus. He earned his Ph.D. in Information Engineering from the Università di Pisa, funded by a prestigious merit-based scholarship from the Islamic Bank Development (IsDB) as Libya's top candidate in 2019-2020. Dr. Elhanashi was a Research Fellow at the University of Strathclyde in 2021, where he applied deep learning models to analyse CT scans and X-ray images for medical diagnostics. In 2022, he was a visiting researcher at Hiroshima University in Japan, focusing on advanced video analysis techniques. With over 16 years of industry experience, he has successfully managed engineering projects, conducted system maintenance, and performed root cause analyses to address technical challenges. He authored the first Arabic-language book on artificial intelligence in Libya and has contributed to numerous peer-reviewed articles in international conferences and journals. He is a developer at the Society for Imaging Informatics in Medicine (SIIM) in USA. His work focuses on real-world AI applications, lightweight model development, video surveillance, IoT-based low-cost embedded systems, designing AI-driven solutions for medical imaging, and efficient coding techniques for imaging and video processing systems.Sergio Saponara, Director of the Department of Information Engineering at the University of Pisa, IEEE Distinguished Lecturer, obtained his Master's degree cum laude and Ph.D. in Electronic Engineering from the University of Pisa. In 2002, he was a Marie Curie Research Fellow at the Inter-university Microelectronics Center (IMEC) in Leuven, Belgium. He was also a post-graduate researcher at the National Research Council. Currently, he is a Full Professor of Electronics at the University of Pisa, where he teaches courses in Vehicular Electronics, Electronic Systems for Robotics, HW and Embedded Security for the Master's degrees in Vehicle Engineering, Robotics and Automation Engineering, and Cybersecurity. Additionally, he teaches Electronics at the Italian Naval Academy in Livorno. Prof. Saponara was President of the Bachelor's and Master's programs in Electronic Engineering at the University of Pisa. He has co-authored 400 scientific articles indexed in Scopus and 20 patents. He is a Founding Member of the IoT CASS SiG and has been a Program Committee Member for over 100 international IEEE and SPIE conferences. He also serves as the Director of the summer school "Enabling Technologies for the Internet of Things (IoT)" and the specialization course "Automotive Electronics and Powertrain Electrification." He is also the Director of the interUniversity Center for Automotive Research (UCAR).

• 1. Introduction2. Image Analysis for Surveillance: Detecting Fire and Smoke Incidents3. Enhancing COVID-19 Safety Measures with AI-Powered Video Analysis4. Deep Learning Approaches for Fingerprint Image Restoration 4.1 Background5. Deep Learning for Classification and Localization of Multiple Abnormalities on chest x-rays images6. Real-time Stroke Detection Based on Deep Learning and Federated Learning7. Efficient Identification of Bag Breakup in Continuous Airflow via Video Analysis