K
Kai Li
Researcher at Nankai University
Publications - 115
Citations - 2001
Kai Li is an academic researcher from Nankai University. The author has contributed to research in topics: Scheduling (computing) & Computer science. The author has an hindex of 20, co-authored 95 publications receiving 1160 citations. Previous affiliations of Kai Li include Instituto Superior de Engenharia do Porto & Sun Yat-sen University.
Papers
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Energy-Efficient Cooperative Relaying for Unmanned Aerial Vehicles
TL;DR: This work proposes an energy-efficient cooperative relaying scheme which extends network lifetime while guaranteeing the success rate, and proposes a computationally efficient suboptimal algorithm to reduce the scheduling complexity.
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Comparison of Transferred Deep Neural Networks in Ultrasonic Breast Masses Discrimination
TL;DR: Cross-validation results have demonstrated that the transfer learning method outperformed the traditional machine learning model and the CNN3 model, where the transferred InceptionV3 achieved the best performance with an accuracy of 85.13% and an AUC of 0.91.
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Wireless Power Transfer and Data Collection in Wireless Sensor Networks
TL;DR: This paper investigates a novel optimal scheduling strategy, called EHMDP, aiming to minimize data packet loss from a network of sensor nodes in terms of the nodes’ energy consumption and data queue state information and shows that the proposed algorithm significantly improves the network performance.
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Energy Efficient Legitimate Wireless Surveillance of UAV Communications
TL;DR: A tracking algorithm is developed for the legitimate UAV to track the suspicious UAV by comprehensively utilizing eavesdropped packets, angle-of-arrival and received signal strength of the suspicious transmitter's signal.
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On-Board Deep Q-Network for UAV-Assisted Online Power Transfer and Data Collection
TL;DR: An on-board deep Q-network is developed to minimize the overall data packet loss of the sensing devices, by optimally deciding the device to be charged and interrogated for data collection, and the instantaneous patrolling velocity of the UAV.