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An Improved Yolo Algorithm Based on Concise Decoupled Head for Real-Time Object Detection in Night Scenarios Cover

An Improved Yolo Algorithm Based on Concise Decoupled Head for Real-Time Object Detection in Night Scenarios

Journal of Artificial Intelligence and Soft Computing Research
Volume 16 (2026): Issue 3 (June 2026)
By: Yanhua Ma,  Ke Lv,  Li-Juan Liu and  Hamid Reza Karimi  
Open Access
|Feb 2026

Authors

Yanhua Ma

School of Integrated Circuits, Dalian University of Technology Liaoning, Dalian, China

Ke Lv

School of Railway Intelligent Engineering, Dalian Jiaotong University Liaoning, Dalian, China

Li-Juan Liu

liulijuan@blcu.edu.cn

School of Information Science, Beijing Language and Culture University Beijing, Beijing, China

Hamid Reza Karimi

Department of Mechanical Engineering, Politecnico di Milano, Milan, Italy
DOI: https://doi.org/10.2478/jaiscr-2026-0011
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Language: English
Page range: 219 - 235
Submitted on: Jun 30, 2025
|
Accepted on: Dec 27, 2025
|
Published on: Feb 25, 2026
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Convolutional block attention module (CBAM),
decoupled head,
structure reparameterization,
YOLO
Related subjects:
Computer sciences,
Databases and data mining,
Artificial intelligence

© 2026 Yanhua Ma, Ke Lv, Li-Juan Liu, Hamid Reza Karimi, published by SAN University
This work is licensed under the Creative Commons Attribution 4.0 License.

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