YOLOv5 with Combination of Coordinate Attention and CBAM for Object Detection on Drone-Reference-Cited by-同舟云学术

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YOLOv5 with Combination of Coordinate Attention and CBAM for Object Detection on Drone

Published:2023-10-16 Issue: Volume: Page:
ISSN:
Container-title:IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society
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Author:

An Jinsu¹,Putro Muhamad Dwisnanto²,Priadana Adri¹,Lee Youlkyeong¹,Kim Junmyeong¹,Jo Kang-Hyun¹

Affiliation:

1. University of Ulsan,Department of Electrical Electronic and Computer Engineering,Ulsan,Korea

2. Universitas Sam Ratulangi,Department of Electrical Engineering,Manado,Indonesia

Funder

National Research Foundation of Korea(NRF)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10311571/10311610/10312634.pdf?arnumber=10312634

Reference27 articles.

1. Coordinate Attention for Efficient Mobile Network Design

2. TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios

3. Focal Loss for Dense Object Detection

4. Cbam: Convolutional block attention module;woo;Proceedings of the European Conference on Computer Vision (ECCV),0

5. ECAP-YOLO: Efficient Channel Attention Pyramid YOLO for Small Object Detection in Aerial Image

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1. Semantic Reliability Maximization: A Cooperative Perspective in Integrated Sensing, Communication and Computation Networks;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04

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