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Shouluan Wu

As seen in: Nature, MDPI
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Articles

River floating object detection with transformer model in real time - Scientific Reports

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By Shouluan Wu
| Nature Verified
Abstract The DEtection TRansformer (DETR) and the YOLO series have been at the forefront of advancements in object detection. The RT-DETR, a member of the DETR family, has notably addressed the speed limitations of its predecessors by utilizing a high-performance hybrid encoder that optimizes query selection. Building upon this foundation, we introduce the LR-DETR, a lightweight evolution of RT-DETR for river floating object detection.
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A Novel YOLOv10-Based Algorithm for Accurate Steel Surface Defect Detection

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By Liefa Liao, Shouluan Wu, Jianglong Fu
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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RS-Xception: A Lightweight Network for Facial Expression Recognition

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By Liefa Liao, Shouluan Wu, Jianglong Fu
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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