Journal of Engineering Research

Artificial intelligence algorithms play a crucial role in computer vision recognition. Improving recognition accuracy and efficiency through continuous algorithm optimization is the current research focus. This paper explores the optimization strategies based on deep learning and their applications in computer vision tasks, including but not limited to image classification, object detection, and semantic segmentation. Firstly, it analyzes the challenges faced by existing algorithms, such as high model complexity and large computational resource requirements, and proposes corresponding solutions, such as adopting lightweight network design and introducing attention mechanisms to enhance performance. The proposed optimization methods can significantly improve the recognition accuracy while maintaining low resource consumption, providing new ideas and directions for subsequent research.

Artificial intelligence; Computer vision; Deep learning; Optimization strategy; Image recognition