1. Bioinspired Artificial Intelligence Applications 2023.
- Author
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Wei, Haoran, Tao, Fei, Huang, Zhenghua, and Long, Yanhua
- Subjects
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ARTIFICIAL intelligence , *DEEP learning , *REINFORCEMENT learning , *MACHINE learning , *DEEP reinforcement learning , *NATURAL language processing - Abstract
This document discusses the rapid development of Artificial Intelligence (AI) and its bioinspired applications. It highlights the benefits of bioinspired AI, such as increased accuracy in image and speech processing, reduced cost and energy usage through edge devices, and enhanced bio-signal quality. However, it also acknowledges the challenges posed by improper AI utilization, such as the generation of fake news and security issues. The document calls for research papers on bioinspired AI applications to explore its potential and address these challenges. It includes examples of research papers that utilize deep reinforcement learning for robot task sequencing, propose a real-time multi-surveillance pedestrian target detection model, develop an intelligent breast mass classification approach, and introduce a bio-inspired object detection algorithm for remote sensing images. The document concludes by emphasizing the importance of biomimetic artificial intelligence in various fields and promoting further research in this area. [Extracted from the article]
- Published
- 2024
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