Enhanced Object Detection Algorithms in Complex Environments via Improved CycleGAN Data Augmentation and AS-YOLO Framework

Object detection in complex environments, such as challenging lighting conditions, adverse weather, and target occlusions, poses significant difficulties for existing algorithms. To address these challenges, this study introduces a collaborative solution integrating improved CycleGAN-based data augm...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Zhen Li, Yuxuan Wang, Lingzhong Meng, Wenjuan Chu, Guang Yang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2025-12-01
Schriftenreihe:	Journal of Imaging
Schlagworte:	image enhancement object detection CycleGAN feature fusion deep learning
Online-Zugang:	https://www.mdpi.com/2313-433X/11/12/447
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