Abstract: With the continuous development of the power system, in the face of the frequency deviation caused by the randomness and volatility of renewable energy sources such as photovoltaic and wind ...
Abstract: Remote sensing images are usually characterized by complex backgrounds, scale and orientation variations, and large intraclass variance. General semantic segmentation methods usually fail to ...
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=5 ...
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=9 ...
Abstract: In this article, an integral reinforcement learning (IRL) method is developed for dynamic event-triggered nonzero-sum (NZS) games to achieve the Nash equilibrium of unmanned surface vehicles ...
Abstract: A method based on deep neural network (DNN) optimized model predictive control (MPC) and standoff fusion is proposed to address the problem of tracking moving target trajectory planning for ...
Abstract: The current optical convolution architectures are facing challenges related to limited scalability, excessive data redundancy and restricted processing bandwidth. In this work, we introduce ...
Abstract: As a cornerstone in the Evolutionary Computation (EC) domain, Differential Evolution (DE) is known for its simplicity and effectiveness in handling challenging black-box optimization ...
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=34 ...
Abstract: The unit quaternion is one of the most commonly utilized attitude representations because of its global representation and singularity-free properties. Nevertheless, the double cover ...
Abstract: Federated Learning (FL) is a distributed machine learning framework that allows multiple clients to collaboratively train an intermediate model with keeping data local, however, sensitive ...
Abstract: The rapid development of deepfake technology poses challenges to face-centered data security. Existing methods primarily focus on how to transfer deepfake detectors from the source domain to ...
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