Research on Image Recognition and Classification Algorithms in Cloud Computing Environment Based on Deep Neural Networks

Image recognition provides an essential role in many areas of modern life, such as security, video analysis, healthcare, and autonomous vehicles. The present article analyzes the evolution of image recognition via the automation of feature extraction processes, leading to the achievement of very sophisticated outcomes. This is achieved by comparing conventional approaches with deep learning methodologies, particularly Convolutional Neural Networks (CNNs). The integration of CNNs with cloud computing has significantly enhanced the speed, scalability, and usability, enabling the real-time analysis of extremely extensive picture datasets. This article discusses significant algorithms, including CNN architectures such as AlexNet, VGG, and ResNet-based models. Transfer learning techniques and the impact of ensemble approaches are also discussed in these articles. Data privacy, security, and the impact of AI on cloud computing are expected to become more critical in the future.