Weiya Shi1,*, Shaowen Zhang2, Shiqiang Zhang2
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3209-3231, 2024, DOI:10.32604/cmes.2023.044863
Abstract In recent years, there has been extensive research on object detection methods applied to optical remote sensing images utilizing convolutional neural networks. Despite these efforts, the detection of small objects in remote sensing remains a formidable challenge. The deep network structure will bring about the loss of object features, resulting in the loss of object features and the near elimination of some subtle features associated with small objects in deep layers. Additionally, the features of small objects are susceptible to interference from background features contained within the image, leading to a decline in detection accuracy. Moreover, the sensitivity of small… More >
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