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A Novel UAV Aerial Vehicle Detection Method Based on Attention Mechanism and Multi-scale Feature Cross Fusion

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Zhiming DingAuthors Info & Claims

AIEE '21: Proceedings of the 2021 2nd International Conference on Artificial Intelligence in Electronics Engineering

Pages 51 - 59

https://doi.org/10.1145/3460268.3460276

Published: 30 July 2021 Publication History

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Abstract

With the rapid development of artificial intelligence science, more and more researchers try to use deep learning to train neural networks and have achieved great success in object detection. Vehicle detection based on UAV image is a special field of object detection. Due to the low resolution of the vehicle object, complex background, and less image information, it is challenging to extract robust visual and spatial features from the depth network and accurately locate the object in complex scenes. In this paper, combining the characteristics of vehicles in aerial images, we design a novel feature pyramid network called channel-spatial attention fused feature pyramid network (CSF-FPN) with Faster R-CNN as the basic framework. In CSF-FPN, a hybrid attention mechanism and feature cross-fusion module are introduced, so that feature maps can be generated with enhanced spatial and channel interdependence to extract richer semantic information. After our CSF-FPN is integrated into the Faster R-CNN network, the detection performance of small objects is greatly improved. The experimental results based on the VEDIA Dataset showed that the proposed framework could effectively detect the vehicle in large scene azimuth. Compared with the existing advanced methods, mAP and F1-score are improved.

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Cited By

Zhou YJiang YYang ZLi XSun WZhen HWang Y(2024)UAV image detection based on multi-scale spatial attention mechanism with hybrid dilated convolution2024 3rd International Conference on Image Processing and Media Computing (ICIPMC)10.1109/ICIPMC62364.2024.10586685(279-284)Online publication date: 17-May-2024
https://doi.org/10.1109/ICIPMC62364.2024.10586685
Zhao CLiu RQu JGao R(2024)Deep learning-based object detection in maritime unmanned aerial vehicle imageryEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.107513128:COnline publication date: 14-Mar-2024
https://dl.acm.org/doi/10.1016/j.engappai.2023.107513
Huang CZheng YZhang J(2024)Deep Landscape Design Evaluation System with Multi-scale Visual Attention MechanismIntelligent 3D Technologies and Augmented Reality10.1007/978-981-97-5184-6_2(13-24)Online publication date: 3-Sep-2024
https://doi.org/10.1007/978-981-97-5184-6_2
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AIEE '21: Proceedings of the 2021 2nd International Conference on Artificial Intelligence in Electronics Engineering

January 2021

102 pages

ISBN:9781450389273

DOI:10.1145/3460268

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 30 July 2021

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AIEE 2021

AIEE 2021: 2021 2nd International Conference on Artificial Intelligence in Electronics Engineering

January 15 - 17, 2021

Phuket, Thailand

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Cited By

Zhou YJiang YYang ZLi XSun WZhen HWang Y(2024)UAV image detection based on multi-scale spatial attention mechanism with hybrid dilated convolution2024 3rd International Conference on Image Processing and Media Computing (ICIPMC)10.1109/ICIPMC62364.2024.10586685(279-284)Online publication date: 17-May-2024
https://doi.org/10.1109/ICIPMC62364.2024.10586685
Zhao CLiu RQu JGao R(2024)Deep learning-based object detection in maritime unmanned aerial vehicle imageryEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.107513128:COnline publication date: 14-Mar-2024
https://dl.acm.org/doi/10.1016/j.engappai.2023.107513
Huang CZheng YZhang J(2024)Deep Landscape Design Evaluation System with Multi-scale Visual Attention MechanismIntelligent 3D Technologies and Augmented Reality10.1007/978-981-97-5184-6_2(13-24)Online publication date: 3-Sep-2024
https://doi.org/10.1007/978-981-97-5184-6_2
Lu FLi KNie YTao YYu YHuang LWang X(2023)Object Detection of UAV Images from Orthographic Perspective Based on Improved YOLOv5sSustainability10.3390/su15191456415:19(14564)Online publication date: 7-Oct-2023
https://doi.org/10.3390/su151914564
Bajpai ASrivastava VYadav SSharma Y(2023)Multiple Flying Object Detection using AlexNet Architecture for Aerial Surveillance Applications2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT56998.2023.10307613(1-6)Online publication date: 6-Jul-2023
https://doi.org/10.1109/ICCCNT56998.2023.10307613
Wu YWang WZhang GYang KChen Y(2023)UAV positioning based on pure azimuth passive2023 IEEE 2nd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA)10.1109/EEBDA56825.2023.10090790(586-590)Online publication date: 24-Feb-2023
https://doi.org/10.1109/EEBDA56825.2023.10090790

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