2 天前 - … The proposed automated AI healthcare system uses resource-efficient deep
learning-inspired architecture for computer vision applications like performing region-wise …

2 天前 - … limited resources of user devices, Mobile Edge Computing (MEC) has emerged.
MEC situates servers at the edge of the mobile network, such as cellular base stations or Wi-Fi …

2 天前 - … This thesis explores the application of machine learning algorithms to address one
of … In order to perform supervised machine learning, wireless communication tool box within …

2 天前 - … equipment (UE) or on a cellular network, for better resource … MEC wireless networks,
an Software Defined Networking (… Deep reinforcement learning for task offloading in mobile …

2 天前 - … In this paper, we explored the innovative application of RL for enhancing security
in … An approach to mitigating sybil attack in wireless networks using zigbee. In 2008 10th …

3 天前 - … propose DeepMIC, a deep reinforcement learning (DRL)-… network information
collected through Software-Defined … congestion in mobile networks and backbone networks [3]. …

3 天前 - … unraveling cellular fate development and heterogeneity. While numerous
machine-learning … Furthermore, the application to human peripheral blood mononuclear cell …

3 天前 - … and uses a random walk-based network propagation … QC, such as quantum machine
learning (QML) methods … can explore complex cellular networks efficiently and potentially …

3 天前 - … ) algorithm for AR applications that mitigates the negative … We first analyze the
impact of wireless communication … issue, AMFL employs a deep reinforcement learning (DRL)-…

3 天前 - … The Internet of Medical Things (IoMT) refers to the application of IoT in health care
and plays … seamless communication with an RFID reader through a wireless sensor network. …