The Evolution of Object Detection Algorithms Based on Deep Learning

Qiyan Guo

2025

Abstract

Object detection technology is an important research direction in the field of computer vision, which is widely used in automatic driving, security monitoring, medical image analysis and other fields. With the rapid development of deep learning technology, object detection algorithms based on deep learning have made significant breakthroughs in accuracy and efficiency, gradually replacing traditional object detection methods. The object detection algorithm based on deep learning can automatically learn features in images and train and optimize them in an end-to-end manner, significantly improving detection accuracy and robustness. The progress of object detection technology is initially reviewed in this study, with particular attention paid to deep learning-based object identification algorithms and conventional object detection techniques. Next, two common deep learning object identification frameworks—YOLO-v3 and Faster R-CNN—are thoroughly examined and contrasted. Experimental results show that YOLO-v3 has a slightly higher average accuracy (mAP) on the COCO dataset than Faster R-CNN, but performs better in small target detection and dense scenarios. Nevertheless, the Faster R-CNN still has some advantages in terms of overall accuracy.

Paper Citation

in Harvard Style

Guo Q. (2025). The Evolution of Object Detection Algorithms Based on Deep Learning. In Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE; ISBN 978-989-758-765-8, SciTePress, pages 199-203. DOI: 10.5220/0013681000004670

in Bibtex Style

@conference{icdse25,
author={Qiyan Guo},
title={The Evolution of Object Detection Algorithms Based on Deep Learning},
booktitle={Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE},
year={2025},
pages={199-203},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013681000004670},
isbn={978-989-758-765-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Science and Engineering - Volume 1: ICDSE
TI - The Evolution of Object Detection Algorithms Based on Deep Learning
SN - 978-989-758-765-8
AU - Guo Q.
PY - 2025
SP - 199
EP - 203
DO - 10.5220/0013681000004670
PB - SciTePress