Researching | Target Detection in Remote Sensing Image Based on Deformable Transformer and Adaptive Detection Head

Laser & Optoelectronics Progress, Volume. 61, Issue 12, 1228006(2024)

Target Detection in Remote Sensing Image Based on Deformable Transformer and Adaptive Detection Head

Haokang Peng¹, Yun Ge^1,2、*, Xiaoyu Yang¹, and Changquan Hu¹

Author Affiliations

¹School of Software, Nanchang Hangkong University, Nanchang 330063, Jiangxi , China

²Jiangxi Huihang Engineering Consulting Co., Ltd., Nanchang 330038, Jiangxi , China

show less

Abstract Get PDF(in Chinese)

Figures&Tables (19)

References (30)

Paper Information

References(30)

[1] Yang X, Wang Q, Yao Y Z et al. Improved aircraft detection of optical remote sensing image based on faster R-CNN[J]. Laser & Optoelectronics Progress, 60, 1228007(2023).

[2] Zhang K, Chen Z J, Qiao D et al. Real-time image detection via remote sensing based on receptive field and feature enhancement[J]. Laser & Optoelectronics Progress, 60, 0228001(2023).

[3] Harris C, Stephens M. A combined corner and edge detector[C], 1-6(1988).

[4] Cortes C, Vapnik V. Support-vector networks[J]. Machine Learning, 20, 273-297(1995).

[5] Nie G T, Huang H. A survey of object detection in optical remote sensing images[J]. Acta Automatica Sinica, 47, 1749-1768(2021).

[6] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

[7] Redmon J, Divvala S, Girshick R et al. You only look once: unified, real-time object detection[C], 779-788(2016).

[8] Redmon J, Farhadi A. YOLOv3: an incremental improvement[EB/OL]. https://arxiv.org/abs/1804.02767

[9] Redmon J, Farhadi A. YOLO9000: better, faster, stronger[C], 6517-6525(2017).

[10] Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: optimal speed and accuracy of object detection[EB/OL]. https://arxiv.org/abs/2004.10934

[11] Lin T Y, Goyal P, Girshick R et al. Focal loss for dense object detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42, 318-327(2020).

[12] Xiang J H, Chen Z X, Wang L Y. Multiscale object detection algorithm for satellite remote-sensing images[J]. Laser & Optoelectronics Progress, 60, 0228003(2023).

[13] Wei X G, Cao L, Tian S et al. Remote sensing target detection based on multi-level self-attention enhancement[J]. Laser & Optoelectronics Progress, 60, 2028004(2023).

[14] Yan J Q, Wang H Q, Yan M L et al. IoU-adaptive deformable R-CNN: make full use of IoU for multi-class object detection in remote sensing imagery[J]. Remote Sensing, 11, 286(2019).

[15] Bao S Z, Zhong X, Zhu R F et al. Single shot anchor refinement network for oriented object detection in optical remote sensing imagery[J]. IEEE Access, 7, 87150-87161(2019).

[16] Liu E H, Zheng Y, Pan B et al. DCL-net: augmenting the capability of classification and localization for remote sensing object detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 59, 7933-7944(2021).

[17] Wu Y, Chen Y P, Yuan L et al. Rethinking classification and localization for object detection[C], 10183-10192(2020).

[18] Song G L, Liu Y, Wang X G. Revisiting the sibling head in object detector[C], 11560-11569(2020).

[19] Zhu X Z, Su W J, Lu L W et al. Deformable DETR: deformable transformers for end-to-end object detection[EB/OL]. https://arxiv.org/abs/2010.04159

[20] Yu J H, Jiang Y N, Wang Z Y et al. UnitBox: an advanced object detection network[C], 516-520(2016).

[21] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C], 770-778(2016).

[22] Vaswani A, Shazeer N, Parmar N et al. Attention is all you need[C], 5998-6008(2017).

[23] Lin T Y, Dollár P, Girshick R et al. Feature pyramid networks for object detection[C], 936-944(2017).

[24] Woo S, Park J, Lee J Y, Ferrari V, Hebert M, Sminchisescu C et al. CBAM: convolutional block attention module[M]. Computer vision-ECCV 2018. Lecture notes in computer science, 11211, 3-19(2018).

[25] Cheng G, Zhou P C, Han J W. Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing, 54, 7405-7415(2016).

[26] Long Y, Gong Y P, Xiao Z F et al. Accurate object localization in remote sensing images based on convolutional neural networks[J]. IEEE Transactions on Geoscience and Remote Sensing, 55, 2486-2498(2017).

[27] Lin T Y, Maire M, Belongie S, Fleet D, Pajdla T, Schiele B et al. Microsoft COCO: common objects in context[M]. Computer vision-ECCV 2014. Lecture notes in computer science, 8693, 740-755(2014).

[28] Rezatofighi H, Tsoi N, Gwak J et al. Generalized intersection over union: a metric and a loss for bounding box regression[C], 658-666(2020).

[29] Zheng Z H, Wang P, Liu W et al. Distance-IoU loss: faster and better learning for bounding box regression[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 12993-13000(2020).

[30] Zhang S F, Chi C, Yao Y Q et al. Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection[C], 9756-9765(2020).

Tools

Get Citation

Copy Citation Text

Haokang Peng, Yun Ge, Xiaoyu Yang, Changquan Hu. Target Detection in Remote Sensing Image Based on Deformable Transformer and Adaptive Detection Head[J]. Laser & Optoelectronics Progress, 2024, 61(12): 1228006

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Remote Sensing and Sensors

Received: Jul. 12, 2023

Accepted: Sep. 7, 2023

Published Online: Jun. 20, 2024

The Author Email: Yun Ge (geyun@nchu.edu.cn)

DOI:10.3788/LOP231702

CSTR:32186.14.LOP231702

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology