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Energy Consumption and Communication Quality Tradeoff for Logistics UAVs: A Hybrid Deep Reinforcement Learning Approach.

, , , and . WCNC, page 1-6. IEEE, (2023)

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Connectivity-Aware 3D UAV Path Design With Deep Reinforcement Learning., , , and . IEEE Trans. Veh. Technol., 70 (12): 13022-13034 (2021)Task Scheduling with Collaborative Computing of MEC System Based on Federated Learning., , , , , , and . VTC Spring, page 1-5. IEEE, (2022)Generating Adversarial Examples with Better Transferability via Masking Unimportant Parameters of Surrogate Model., , , and . IJCNN, page 1-8. IEEE, (2023)Proactive eavesdropping rate maximization with UAV spoofing relay., , , , , and . Phys. Commun., (2022)Pose2Seg: Detection Free Human Instance Segmentation., , , , , , , , and . CVPR, page 889-898. Computer Vision Foundation / IEEE, (2019)Energy Trade-off in Ground-to-UAV Communication via Trajectory Design., , , and . CoRR, (2017)Secure two-way transmission via untrusted UAV Relay: Joint path design and slot-pairing strategy., , , , , and . Comput. Networks, (December 2023)DP-Net: Dynamic Programming Guided Deep Neural Network Compression., , , , , and . CoRR, (2020)Dynamic Programming Assisted Quantization Approaches for Compressing Normal and Robust DNN Models., , , and . ASP-DAC, page 351-357. ACM, (2021)3D Radio Map Reconstruction and Trajectory Optimization for Cellular-Connected UAVs., , , , and . J. Commun. Inf. Networks, 8 (4): 357-368 (December 2023)