Optoelectronics Letters, Volume. 21, Issue 4, 226(2025)
Multi-scale feature fusion optical remote sensing target detection method
[1] [1] LIU X B, LIU P, CAI Z H, et al. Research progress of object detection in optical remote sensing images based on deep learning[J]. Acta automatica sinica, 2021, 47(09): 2078-2089.
[2] [2] HUANG Y B. Research on remote sensing image object detection method based on deep neural network[D]. Hangzhou: Hangzhou Dianzi University, 2023. (in Chinese)
[3] [3] XU W. Research and implementation of remote sensing image detection technology based on convolutional neural network[D]. Beijing: Beijing University of Posts and Telecommunications, 2023. (in Chinese)
[4] [4] NAWAZ S A, LI J B, BHATTI U A, et al. AI-based object detection latest trends in remote sensing, multimedia and agriculture applications[J]. Frontiers in plant science, 2022, 13: 1041514.
[5] [5] ZHENG J, HU X B, WEI S Y, et al. Remote sensing object detection technology based on deep learning[J]. Computer engineering and design, 2019, 45(02): 594-600.
[6] [6] YU M, CHENG M, JIANG H, et al. Multi-scale object detection in optical remote sensing images using atrous feature pyramid network[C]//The 27th International Conference on Neural Information Processing (ICONIP 2020), November 18-22, 2020, online. Cham: Springer, 2020.
[7] [7] LIU S, ZHANG L, LU H C, et al. Center-boundary dual attention for oriented object detection in remote sensing images[J]. IEEE transactions on geoscience and remote sensing, 2022, 60: 1-14.
[8] [8] YANG Y R. Vehicle target detection algorithm based on improved faster R-CNN for remote sensing images[J]. Journal of artificial intelligence practice, 2024, 7(1): 27-33.
[9] [9] HE D, SHI Q, LIU X, et al. Generating 2m fine-scale urban tree cover product over 34 metropolises in China based on deep context-aware sub-pixel mapping network[J]. International journal of applied earth observation and geoinformation, 2022, 106: 102667.
[10] [10] GE J, WANG C, ZHANG B, et al. Azimuth-sensitive object detection of high-resolution SAR images in complex scenes by using a spatial orientation attention enhancement network[J]. Remote sensing, 2022, 14(9): 2198.
[11] [11] HU Z, YANG H, LOU T. Dual attention-guided feature pyramid network for instance segmentation of group pigs[J]. Computers and electronics in agriculture, 2021, 186: 106140.
[12] [12] LAN J H, ZHANG C, LU W J, et al. Spatial-transformer and cross-scale fusion network (STCS-Net) for small object detection in remote sensing images[J]. Journal of the Indian society of remote sensing, 2023, 51(7): 1427-1439.
[13] [13] SHI W Y, ZHANG S W, ZHANG S Q. CAW-YOLO: cross-layer fusion and weighted receptive field-based YOLO for small object detection in remote sensing[J]. Computer modeling in engineering & sciences, 2024, 139(3): 3209-3231.
[14] [14] HUANG W, LI G, CHEN Q, et al. CF2PN: a cross-scale feature fusion pyramid network based remote sensing target detection[J]. Remote sensing, 2021, 13(5): 847.
[15] [15] ANDRZEJ S, GORU U K, GARIKAPATI B D, et al. Spiral search grasshopper features selection with VGG19-ResNet50 for remote sensing object detection[J]. Remote sensing, 2022, 14(21): 5398.
[16] [16] LIN T Y, DOLLAR P, GIRSHICK R, et al. Feature pyramid networks for object detection[C]//IEEE Conference on Computer Vision and Pattern Recognition, July 21-26, 2017, Hawaii, USA. New York: IEEE, 2017: 2117-2125.
[17] [17] SUN H T, YANG S, CHEN L J, et al. Brain tumor image segmentation based on improved FPN[J]. BMC medical imaging, 2023, 23(1): 172.
[18] [18] JIANG Y Q, TAN Z Y, WANG J Y. GiraffeDet: a heavy-neck paradigm for detection in remote sensing images using progressive anchor boxes[J]. Remote sensing, 2021, 13(8): 1447.
[19] [19] QIU X. U-Net-ASPP: U-Net based on atrous spatial pyramid pooling model for medical image segmentation in COVID-19[J]. Journal of applied science and engineering, 2022, 25(6): 1167-1176.
[20] [20] PARK M H, CHO J H, KIM Y T. CNN model with multilayer ASPP and two-step cross-stage for semantic segmentation[J]. Machines, 2023, 11(2): 126.
[21] [21] WANG H L, GUI D W, LIU Q, et al. Vegetation coverage precisely extracting and driving factors analysis in drylands[J]. Ecological informatics, 2024, 79: 102409.
Get Citation
Copy Citation Text
BAI Liang, DING Xuewen, LIU Ying, CHANG Limei. Multi-scale feature fusion optical remote sensing target detection method[J]. Optoelectronics Letters, 2025, 21(4): 226
Received: Mar. 11, 2024
Accepted: Feb. 28, 2025
Published Online: Feb. 28, 2025
The Author Email: