Abstract: Deep learning for change detection is one of the current hot topics in the field of remote sensing. However, most end-to-end networks are proposed for supervised change detection, and ...
Abstract: Recently, deep-learning-based fault diagnosis methods have been widely studied for rolling bearings. However, these neural networks are lack of interpretability for fault diagnosis tasks.
Abstract: This article addresses the security problem of tracking control for nonlinear multiagent systems against jamming attacks. It is assumed that the communication networks among agents are ...
Abstract: Large Language Models (LLMs) recently demonstrated extraordinary capability in various natural language processing (NLP) tasks including language translation, text generation, question ...
Abstract: The regional integration of variable wind power could be restricted by a strong coupling of electric power generation dispatch and heat supply of combined heat-and-power (CHP) units. The ...
Abstract: In this communication, a dual-band aperture-shared antenna array (ASAA) is developed for base station. This ASAA contains a 4 $\times $ 4 high-band (HB) antenna array, which operates from ...
Abstract: So far, all existing offshore wind farms have an ac collection system, and the collected power in the offshore wind farm is sent to an onshore ac grid through high-voltage ac (HVAC) or DC ...
Abstract: Network automation has been bred by the deployment of 5G based Industrial Internet-of-Things (IIoT) in Industry 4.0, and further approaching pervasive AI ...
Abstract: This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour ...
Abstract: When more circuit functions are integrated into a single chip fabricated by the GaN-on-Silicon process, the need for on-chip electrostatic discharge (ESD) protection design becomes crucial ...
Abstract: For hyperspectral image (HSI) change detection (CD), multiscale features are usually used to construct the detection models. However, the existing studies only consider the multiscale ...
Abstract: Existing geometric knowledge graph embedding methods employ various relational transformations, such as translation, rotation, and projection, to model different relation patterns, which ...
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