Research on the optimization and application of artificial intelligence algorithms in computer vision recognition
人工智能算法在计算机视觉识别中的优化与应用研究

摘要

人工智能算法在计算机视觉识别中扮演着至关重要的角色，通过不断优化算法来提升识别精度与效率是当前研究的重点。本文探讨了基于深度学习的优化策略及其在计算机视觉任务中的应用，包括但不限于图像分类、目标检测和语义分割等。首先分析了现有算法面临的挑战，如模型复杂度高、计算资源需求大等，并提出相应的解决方案，如采用轻量级网络设计、引入注意力机制等以提高性能。所提出的优化方法能够在保持较低资源消耗的同时显著提升识别准确率，为后续研究提供了新的思路与方向。

Abstract

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.