Applications of Distributed Machine Learning for the Internet-of-Things: A Comprehensive Survey
The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
Determination of the severity and percentage of COVID-19 infection through a hierarchical deep learning system
The coronavirus disease 2019 (COVID-19) has caused millions of deaths and one of the
greatest health crises of all time. In this disease, one of the most important aspects is the …
greatest health crises of all time. In this disease, one of the most important aspects is the …
Modern image-guided surgery: A narrative review of medical image processing and visualization
Z Lin, C Lei, L Yang - Sensors, 2023 - mdpi.com
Medical image analysis forms the basis of image-guided surgery (IGS) and many of its
fundamental tasks. Driven by the growing number of medical imaging modalities, the …
fundamental tasks. Driven by the growing number of medical imaging modalities, the …
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging
Selective experience replay is a popular strategy for integrating lifelong learning with deep
reinforcement learning. Selective experience replay aims to recount selected experiences …
reinforcement learning. Selective experience replay aims to recount selected experiences …
Multi-agent deep reinforcement learning for distributed load restoration
This paper addresses the load restoration problem after power outage events. Our primary
proposed methodology is using multi-agent deep reinforcement learning to optimize the …
proposed methodology is using multi-agent deep reinforcement learning to optimize the …
Machine learning in handling disease outbreaks: a comprehensive review
D Riswantini, E Nugraheni - Bulletin of Electrical Engineering and …, 2022 - beei.org
The changes in the global environment have made impact on the evolution of infectious
diseases, virus mutations, or new diseases which are challenging to be tackled with new …
diseases, virus mutations, or new diseases which are challenging to be tackled with new …
Integrated clinical environment security analysis using reinforcement learning
Many communication standards have been proposed recently and more are being
developed as a vision for dynamically composable and interoperable medical equipment …
developed as a vision for dynamically composable and interoperable medical equipment …
[HTML][HTML] A survey on multi-agent reinforcement learning and its application
Multi-agent reinforcement learning (MARL) has been a rapidly evolving field. This paper
presents a comprehensive survey of MARL and its applications. We trace the historical …
presents a comprehensive survey of MARL and its applications. We trace the historical …
Hybrid Diagnostic Model for Improved COVID-19 Detection in Lung Radiographs Using Deep and Traditional Features
A recently discovered coronavirus (COVID-19) poses a major danger to human life and
health across the planet. The most important step in managing and combating COVID-19 is …
health across the planet. The most important step in managing and combating COVID-19 is …
A review of research on reinforcement learning algorithms for multi-agents
K Hu, M Li, Z Song, K Xu, Q Xia, N Sun, P Zhou, M Xia - Neurocomputing, 2024 - Elsevier
In recent years, multi-agent reinforcement learning techniques have been widely used and
evolved in the field of artificial intelligence. However, traditional reinforcement learning …
evolved in the field of artificial intelligence. However, traditional reinforcement learning …