YOLOv8 for Object Detection: A Comprehensive Review of Advances,Techniques, and Applications
DOI:
https://doi.org/10.71129/ijaci.v2i1.pp53-61Keywords:
YOLOv8, Object Detection , Data Augmentation , Deep Learning, Computer VisionAbstract
This paper presents a review focusing on the most current advancements in object detection techniques using YOLOv8 and their applications across a range of fields, such as surveillance systems, autonomous driving, smart agriculture, industrial quality control, and medical image analysis. YOLOv8, launched by Ultralytics in early 2023, represents the newest evolution of the You Only Look Once framework., YOLOv8 demonstrates notable improvements in both detection accuracy and processing speed compared to earlier versions. This review explores key updates in YOLOv8’s architecture, including enhanced backbone designs, efficient training processes, and optimized loss functions, alongside the incorporation of attention mechanisms and compact model structures. These findings from 40+ selected studies confirm YOLOv8’s potential as a reliable and efficient solution for object detection tasks in both academic research and real-world applications. This study serves as a comprehensive reference for researchers and practitioners seeking to optimize aiming to enhance YOLOv8-based models across diverse practical applications.
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Copyright (c) 2026 Vivi Afifah, Surni Erniwati (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.


