Imagex, as an image processing technology, is widely used in the field of artificial intelligence. Its underlying technical support is the key to its efficient and accurate operation. This article will deeply explore the support and impact of Imagex's underlying technology, and analyze its important role in image processing and applications. Imagex's underlying technologies include deep learning, convolutional neural networks (CNN), and natural language processing (NLP). Deep learning is a machine learning algorithm based on artificial neural networks. Through layer-by-layer processing and learning, it can simulate the operation of the human brain. Deep learning technology is the cornerstone of Imagex's image recognition, classification and processing. Through a large number of training samples and algorithm optimization, Imagex can process images efficiently and accurately in various scenarios. Convolutional neural network (CNN) is an important architecture of deep learning and plays an important role in image processing. The design of CNN is inspired by the working principle of the human visual system. It is constructed through a series of convolutional layers, pooling layers and fully connected layers to extract features and abstract images. Imagex uses CNN technology to analyze, understand and process images to achieve functions such as face recognition, object detection, and scene analysis. Through the outstanding capabilities of CNN, Imagex can achieve efficient and accurate results when processing large-scale image data. Natural language processing (NLP) technology is another important component of Imagex's underlying technology. NLP technology is a technology for modeling and processing human language cognition and understanding. Imagex uses NLP technology to convert natural language into a machine-processable form to realize the understanding and processing of voice commands. This allows Imagex to implement functions such as voice assistants and smart customer service, providing users with a convenient voice interaction experience. In addition to underlying technical support such as deep learning, CNN and NLP, Imagex also relies on infrastructure such as big data and high-performance computing. Big data technology provides Imagex with a large amount of data training and learning, allowing it to extract effective features from large-scale data. High-performance computing technology provides powerful computing capabilities to accelerate Imagex's image processing and analysis process. The support of Imagex underlying technology has an important impact on image processing and application fields. It plays a key role in many industries and fields. For example, in face recognition technology, Imagex uses underlying technology to achieve accurate face recognition and authentication. In the field of medical imaging, Imagex's underlying technology supports doctors in analyzing and diagnosing disease images. In smart transportation systems, Imagex provides vehicle and pedestrian identification and tracking through underlying technologies. However, the underlying technology of Imagex still faces some challenges. For example, for factors such as complex scenes, lighting conditions, and angle changes, Imagex may have problems with recognition errors and performance degradation. In addition, issues such as privacy protection and data security also need to be fully considered and resolved. In summary, the support of Imagex's underlying technology is the key to its implementation of image processing and applications.