Computer vision is a field of artificial intelligence (AI) that focuses on enabling machines to understand and interpret visual information, such as images and videos, similar to how humans do. The goal of computer vision is to allow machines to recognize objects, detect patterns, and analyze scenes, which can then be used to make decisions or perform tasks. For example, in image classification, computer vision models can identify the contents of an image, such as distinguishing between a cat and a dog. Another application is object detection, where the system identifies and locates objects in an image, such as recognizing and marking the location of pedestrians in a self-driving car’s camera feed. Facial recognition is another well-known use of computer vision, where systems can identify or verify a person’s identity based on facial features. Overall, computer vision leverages algorithms like convolutional neural networks (CNNs) to process and understand visual data, making it an essential tool in applications across healthcare, automotive, and security sectors.
What is computer vision?

- Accelerated Vector Search
- How to Pick the Right Vector Database for Your Use Case
- The Definitive Guide to Building RAG Apps with LlamaIndex
- Information Retrieval 101
- Vector Database 101: Everything You Need to Know
- 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 theoretical foundations behind DDIM?
Denoising Diffusion Implicit Models (DDIM) are rooted in the framework of diffusion processes, which are used to model t
How does observability handle caching layers in databases?
Observability in the context of databases, particularly with caching layers, involves monitoring and understanding how c
Can federated learning work with unsupervised learning tasks?
Yes, federated learning can work with unsupervised learning tasks. Federated learning is a machine learning approach tha