摘要
Abstract
This study explores around data-driven artificial intelligence image processing techniques,and designs a deep learning-based processing model for image denoising and super-resolution reconstruction tasks.By introducing an improved attention mechanism,the model's ability to capture image details is enhanced and the effectiveness of feature extraction is enhanced.Experiments on public datasets show that the improved model gains in processing accuracy and computational efficiency,and exhibits good environmental adaptability and stability in practical application scenarios,providing new ideas for the development of data-driven image processing technology.关键词
深度学习/图像处理/注意力机制/数据驱动Key words
deep learning/image processing/attention mechanism/data-driven分类
信息技术与安全科学
