Abstract: A new fault detection technique for power transformers using Walsh matrix analysis and a feedforward neural network is presented. Initially, Walsh coefficients are computed from the Walsh ...
Transformers are a neural network (NN) architecture, or model, that excels at processing sequential data by weighing the importance of different parts of the input sequence. This allows them to ...
Abstract: This paper proposes a feedforward compensation strategy based on Parallel GRU-Transformer neural network to address the issues of large tracking errors and insufficient stability of multi ...
Transformer models and end-to-end learning frameworks are rapidly revolutionizing the field of artificial intelligence. In this work, we apply object detection transformers to analyze charge stability ...
The First Hospital of Hunan University of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China Background: Breast cancer remains the most prevalent malignancy in women globally, ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. To address the challenges in FCS data fitting, we propose a ...
Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...
School of Electric Power Engineering, South China University of Technology, Guangzhou, China In order to enhance self-monitoring and self-diagnosis capabilities in smart distribution networks, this ...
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