The goal of object detection is to identify and locate objects within an image or video. It involves determining the class of each object and marking its position, typically using bounding boxes. Object detection is a foundational task in computer vision with applications in various fields. For instance, it enables autonomous vehicles to detect pedestrians, traffic signs, and other vehicles. In surveillance, it is used to identify intruders or suspicious activities in real time. Advanced algorithms, such as YOLO (You Only Look Once) and Faster R-CNN, make object detection efficient and accurate. These methods are critical for real-world applications, where both precision and speed are essential for decision-making and safety.
What is the goal of object detection?

- Embedding 101
- The Definitive Guide to Building RAG Apps with LlamaIndex
- AI & Machine Learning
- Vector Database 101: Everything You Need to Know
- GenAI Ecosystem
- 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 does AutoML support active learning?
AutoML, or Automated Machine Learning, supports active learning by streamlining the process of selecting the most inform
What are the differences between LangChain and other LLM frameworks like LlamaIndex or Haystack?
LangChain, LlamaIndex, and Haystack are frameworks designed for working with large language models (LLMs), but each has
How do serverless platforms enable continuous integration?
Serverless platforms facilitate continuous integration (CI) by streamlining the deployment process and automating many t