Vision processing in AI involves analyzing and interpreting visual data, such as images and videos, to extract meaningful information. This process typically includes tasks like image preprocessing, feature extraction, and applying machine learning models for tasks like classification, segmentation, or object detection. Vision processing is integral to applications like facial recognition, autonomous vehicles, and augmented reality. Techniques such as convolutional neural networks (CNNs) and transformers are commonly used for vision processing in modern AI systems, enabling them to handle large-scale and complex visual data.
What is vision processing in AI?

- Retrieval Augmented Generation (RAG) 101
- AI & Machine Learning
- GenAI Ecosystem
- Mastering Audio AI
- Exploring Vector Database Use Cases
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
How do multi-agent systems support smart grids?
Multi-agent systems (MAS) play a crucial role in supporting smart grids by enabling decentralized control, improving com
Can Agentic AI handle complex multi-step workflows autonomously?
Yes, Agentic AI can handle complex multi-step workflows autonomously, but only when those workflows are carefully scoped
How do knowledge graphs enable connected data?
Knowledge graphs enable connected data by creating a structured way to represent information and the relationships betwe