Object proposal in object detection refers to the process of generating candidate regions in an image that are likely to contain objects. These regions are then analyzed in detail to determine their contents and classifications. The purpose of object proposals is to reduce the computational load by narrowing down the regions of interest. For example, instead of scanning every pixel in an image, the system identifies and processes potential object-containing areas. Techniques like selective search and edge boxes are commonly used for this task. Object proposals play a critical role in modern object detection frameworks, such as Faster R-CNN. By providing a manageable number of candidate regions, they allow the model to focus on these areas, making object detection both faster and more efficient.
What is the definition of Object proposal in object detection?
- The Definitive Guide to Building RAG Apps with LlamaIndex
- How to Pick the Right Vector Database for Your Use Case
- Information Retrieval 101
- Mastering Audio AI
- 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 steps does DeepSeek take to prevent data breaches?
DeepSeek implements multiple layers of security measures to prevent data breaches, focusing on both technical and admini
What is a hybrid recommender system?
A hybrid recommender system combines multiple recommendation techniques to improve the accuracy and relevance of suggest
How does a convolutional neural network (CNN) work?
A convolutional neural network (CNN) is a specialized type of neural network primarily designed for processing grid-like