In this paper, a novel visual image real-time detection LSE-Yolo neural network is presented, which is in artificial intelligence-based Internet of Things for smart cites and smart homes. Despite the great achievements that have been acquired in image detection, the issue of visual image real-time detection combined with privacy data protection to serve for smart cities and smart homes has been overlooked. The technique we applied in our study is referred to as visual object detection, which can contribute to more healthy and comfortable life. When several studies have been carried out to test the validity, it is suggested that our proposed LSE-Yolo neural network has better performance in image real-time detection based on AIoT for smart cities and smart homes. And it is similar to state-of-the-art. The fruitful work has made great contributions to our present understanding of the visual image detection serving for smart cities and smart homes.
CITATION STYLE
Zhi-Xian, Z., & Zhang, F. (2022). Image Real-Time Detection Using LSE-Yolo Neural Network in Artificial Intelligence-Based Internet of Things for Smart Cities and Smart Homes. Wireless Communications and Mobile Computing, 2022. https://doi.org/10.1155/2022/2608798
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