Computer vision enables machines to interpret and process visual information, finding applications across diverse domains. In healthcare, it is used for medical imaging tasks like detecting tumors in X-rays or MRIs. In security, it supports facial recognition systems and surveillance monitoring. Computer vision plays a key role in automation. In manufacturing, for instance, it identifies defective items on assembly lines. Self-driving cars rely on computer vision to detect and interpret road signs, obstacles, and lane markings. Agricultural uses include monitoring crop health using drone images. Another significant application is in consumer technology. Smartphones employ computer vision for augmented reality (AR), enabling users to overlay virtual objects on real-world scenes. Retail applications include visual search, where shoppers upload images to find similar products online.
What are the applications of computer vision?
- How to Pick the Right Vector Database for Your Use Case
- Exploring Vector Database Use Cases
- Natural Language Processing (NLP) Basics
- Optimizing Your RAG Applications: Strategies and Methods
- Getting Started with Zilliz Cloud
- 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 is the difference between discrete and continuous diffusion models?
Discrete and continuous diffusion models are two approaches used to describe how information, materials, or phenomena sp
How do you detect bias in embeddings?
Detecting bias in embeddings involves evaluating how embeddings reflect various demographic or societal biases, such as
How do you implement knowledge graph-based search engines?
To implement a knowledge graph-based search engine, you begin by building the knowledge graph itself. A knowledge graph