Application of convolutional neural network in digital image processing technology

With the gradual improvement of the digital level in modern society, image data plays an important role in many industries and fields with its intuitive, vivid and rich characteristics. However, the rapid accumulation and wide spread of image data has also brought severe challenges to the traditional image processing technology, especially in the processing of large-scale and high-complexity image data, which can no longer meet the high standard requirements of practical application projects for efficiency and accuracy. In this regard, based on the current demand, this study will deeply explore the feasibility and effectiveness of convolutional neural network (CNN) technology in the field of image processing, and select examples to further verify the application strategies and implementation methods of CNN in different image processing tasks, so as to promote the integration, transformation and upgrading of digital image processing technology. Practice has proved that CNN, with its excellent feature extraction and learning ability, can play an important role in the key tasks of image segmentation, which has a wide application prospect and important research value.