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27 June 2023 An improved YOLOX for remote sensing image object detection
Zhou Fang, Lin He, Yingqi Li
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Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 1270505 (2023) https://doi.org/10.1117/12.2680392
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China
Abstract
Recent studies have shown that the attention mechanism can further improve the detection accuracy of YOLOX algorithm in remote sensing images, and coordinate attention can well solve the long-range dependencies problem of the previous attention modules, but its attention weights is too redundant in the channel dimension. At the same time, there is a problem of example imbalance in the training of YOLOX algorithm for remote sensing image object detection. To solve the above problems, an improved YOLOX algorithm is proposed, which combines the improved coordinate attention and focal loss. The former not only further adopts pooling and convolution operations to make the attention weights no longer contain redundant channel information when it still has the potential to capture long-range dependencies, but also introduces 1D convolution layers to obtain the final attention weights in three different directions to make the model pay more attention to the effective parts of the features of remote sensing images. The latter optimizes the quality of the gradients, which makes the training more effective and improves the detection accuracy. Training and testing with open remote sensing image dataset. The detection results show the effectiveness and superiority of our method.
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Zhou Fang, Lin He, and Yingqi Li "An improved YOLOX for remote sensing image object detection", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 1270505 (27 June 2023); https://doi.org/10.1117/12.2680392
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KEYWORDS
Object detection
Education and training
Remote sensing
Detection and tracking algorithms
Convolution
Image quality
Feature extraction
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