Efficiency improvement strategy of artificial intelligence algorithm in image recognition system
人工智能算法在图像识别系统中的效率提升策略

摘要

随着人工智能技术的飞速发展，图像识别系统在众多领域得到广泛应用。其效率问题亟待解决。本文从算法优化、硬件加速、数据增强和模型压缩四个方面探讨提升图像识别系统效率的策略。通过优化算法结构、利用硬件资源、丰富数据集和压缩模型规模，可显著提高系统效率。实验结果表明，这些策略在准确率和速度上均取得良好效果，为图像识别系统的发展提供了有力支持。

Abstract

With the rapid development of artificial intelligence technology, image recognition systems have been widely applied in many fields. However, their efficiency remains a pressing issue. This paper explores strategies to enhance the efficiency of image recognition systems from four aspects: algorithm optimization, hardware acceleration, data augmentation, and model compression. By optimizing algorithm structures, utilizing hardware resources, enriching datasets, and reducing model size, system efficiency can be significantly improved. Experimental results show that these strategies achieve good performance in both accuracy and speed, providing strong support for the development of image recognition systems.