Abstract: In industry, the automatic recognition of surface defects of flat steel products still represents a real challenge. Indeed, in addition to constraints such as the image noise or blur, there ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...

A comprehensive comparative study of deep learning architectures for Human Activity Recognition (HAR) using the UCI-HAR dataset. This research evaluates the performance of CNN-LSTM, attention ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...

1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...

Abstract: This study presents an innovative approach to detect and classify four types of rice leaf diseases, including bacterial leaf blight, brown spot, tungro, and blast, as well as healthy leaves, ...

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NFL analyst Kevin Clark recently compared Patrick Mahomes' deep ball accuracy to that of Daniel Jones and Cooper Rush. Surprisingly, Mahomes averaged only 6.2 yards downfield per attempt last season, ...

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...