Computer vision technology has a wide range of applications across different industries. One common use case is autonomous vehicles, where computer vision is used to process images from cameras and LiDAR sensors to detect objects like pedestrians, other vehicles, and road signs. This helps the car make real-time decisions to navigate safely. Another key use case is in medical imaging. Computer vision is employed to analyze X-rays, MRIs, and CT scans to detect abnormalities such as tumors, fractures, and infections, assisting healthcare professionals in diagnostics. In retail, computer vision is used for inventory management, allowing automated systems to track stock levels and even detect misplaced items on shelves. It also plays a role in security and surveillance. Cameras equipped with computer vision systems can automatically identify suspicious activity or people, making monitoring more efficient. In manufacturing, computer vision is used in quality control to detect defects in products on assembly lines, ensuring only high-quality products reach consumers. Furthermore, face recognition technology is used in various fields, from unlocking smartphones to enhancing security in airports. Agriculture is another area where computer vision assists with monitoring crop health and detecting pests, enabling more precise farming practices. These use cases highlight the versatility and potential of computer vision in solving real-world problems.
What are the use cases of computer vision technology?

- The Definitive Guide to Building RAG Apps with LlamaIndex
- Large Language Models (LLMs) 101
- Vector Database 101: Everything You Need to Know
- The Definitive Guide to Building RAG Apps with LangChain
- Evaluating Your RAG Applications: Methods and Metrics
- 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
What are the challenges of designing AI agents?
Designing AI agents poses several challenges that developers must navigate to create effective and reliable systems. One
What is the role of transfer learning in zero-shot learning?
Transfer learning plays a crucial role in zero-shot learning by leveraging knowledge gained from one task to improve per
What are some real-world examples of knowledge graph applications?
Knowledge graphs are powerful tools for organizing and representing information about entities and their relationships.