Learnable Cross-Scale Sparse Attention Guided Feature Fusion for UAV Object Detection-Reference-Cited by-同舟云学术

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Learnable Cross-Scale Sparse Attention Guided Feature Fusion for UAV Object Detection

Published:2024 Issue: Volume:12 Page:114212-114226
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zuo Xin¹,Qi Chenhui¹,Chen Yifei²,Shen Jifeng²^ORCID,Fan Heng³^ORCID,Yang Wankou⁴^ORCID

Affiliation:

1. School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, China

2. School of Electronic and Informatics Engineering, Jiangsu University, Zhenjiang, China

3. Department of Computer Science and Engineering, University of North Texas, Denton, TX, USA

4. School of Automation, Southeast University, Nanjing, Jiangsu, China

Funder

National Natural Science Foundation of China

NSF of Jiangsu Province, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10638027.pdf?arnumber=10638027

Reference68 articles.

1. Multi-target detection and tracking from a single camera in Unmanned Aerial Vehicles (UAVs)

2. Target detection approach for UAVs via improved Pigeon-inspired Optimization and Edge Potential Function

3. Vision-Based Target Detection and Localization via a Team of Cooperative UAV and UGVs

4. SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water

5. Feature Pyramid Networks for Object Detection

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