Object detection in computer vision refers to the task of identifying and locating objects within an image or video. The goal is to not only classify the objects present but also to determine their precise location by drawing bounding boxes around them. Object detection combines techniques from image classification, which identifies what an object is, and localization, which indicates where it is within the image. Examples include detecting people, cars, or animals in images. Modern object detection algorithms, such as YOLO (You Only Look Once) or SSD (Single Shot MultiBox Detector), have become popular due to their accuracy and speed. These models work by processing the entire image at once, allowing them to detect multiple objects in one pass. Applications of object detection include facial recognition in security systems, tracking moving objects in autonomous vehicles, and identifying defective items on assembly lines in manufacturing. Object detection is one of the most important tasks in computer vision and has wide-ranging applications across various industries.
What is object detection in computer vision?
- How to Pick the Right Vector Database for Your Use Case
- GenAI Ecosystem
- Retrieval Augmented Generation (RAG) 101
- Natural Language Processing (NLP) Basics
- Master Video AI
- 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 diffusion models handle different types of noise during sampling?
Diffusion models, a class of generative models, operate by transforming random noise into data through a series of gradu
How does AutoML simplify hyperparameter optimization?
AutoML simplifies hyperparameter optimization by automating the process of selecting the best hyperparameters for machin
How does federated learning handle device heterogeneity?
Federated learning addresses device heterogeneity by designing algorithms that can adapt to the varying capabilities of