Applied Analysis Study of Computer Vision Detection Technology

Applied Analysis Study of Computer Vision Detection Technology

Authors

  • Fu Wang Wenzhou Industrial Science Research Institute, Wenzhou 325000, Zhejiang

DOI:

https://doi.org/10.53469/ijomsr.2025.08(06).04

Keywords:

Computer, Visual detection technology, The application is available

Abstract

With the continuous improvement of China's economic development level, computer technology is developing rapidly and has made great progress, and its application in various fields is becoming more and more widespread. It has become an important tool in people's lives, even at work. With the appearance of computer technology, computer vision recognition technology has greatly promoted the development of image processing technology and provided additional technical support for image processing.

References

Fang, Z. (2025). Adaptive QoS‐Aware Cloud–Edge Collaborative Architecture for Real‐Time Smart Water Service Management.

Qi, R. (2025). DecisionFlow for SMEs: A Lightweight Visual Framework for Multi-Task Joint Prediction and Anomaly Detection.

Wang, Y. (2025). Efficient Adverse Event Forecasting in Clinical Trials via Transformer-Augmented Survival Analysis.

Guo, Haocheng, Yaqiong Zhang, Lieyang Chen, and Arfat Ahmad Khan. "Research on Vehicle Detection Based on Improved YOLOv8 Network." Applied and Computational Engineering 116 (2025): 161-167.

Jin, Yuhui, Yaqiong Zhang, Zheyuan Xu, Wenqing Zhang, and Jingyu Xu. "Advanced object detection and pose estimation with hybrid task cascade and high-resolution networks." In 2024 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML), pp. 1293-1297. IEEE, 2024.

Zhang, Shengyuan, et al. "Research on machine learning-based anomaly detection techniques in biomechanical big data environments." Molecular & Cellular Biomechanics 22.3 (2025): 669-669.

Saunders, E., Zhu, X., Wei, X., Mehta, R., Chew, J., & Wang, Z. (2025). The AI-Driven Smart Supply Chain: Pathways and Challenges to Enhancing Enterprise Operational Efficiency. Journal of Theory and Practice in Economics and Management, 2(2), 63–74. https://doi.org/10.5281/zenodo.15280568

Pal, P. et al. 2025. AI-Based Credit Risk Assessment and Intelligent Matching Mechanism in Supply Chain Finance. Journal of Theory and Practice in Economics and Management. 2, 3 (May 2025), 1–9. DOI:https://doi.org/10.5281/zenodo.15368771

Qi, R. (2025). Interpretable Slow-Moving Inventory Forecasting: A Hybrid Neural Network Approach with Interactive Visualization.

Wang, Y. (2025). RAGNet: Transformer-GNN-Enhanced Cox–Logistic Hybrid Model for Rheumatoid Arthritis Risk Prediction.

Ding, Y., Wang, X., Yuan, H., Qu, M., & Jian, X. (2025). Decoupling feature-driven and multimodal fusion attention for clothing-changing person re-identification. Artificial Intelligence Review, 58(8), 1-26.

Ma, Haowei, Cheng Xu, and Jing Yang. "Design of Fine Life Cycle Prediction System for Failure of Medical Equipment." Journal of Artificial Intelligence and Technology 3.2 (2023): 39-45.

Downloads

Published

2025-06-16

Issue

Section

Articles
Loading...