Predefined boxes of various sizes and ratios serving as references for object detection.
This concept is essential for understanding computer vision and forms a key part of modern AI systems.
Related Concepts
- Object Detection
- Bounding Box
- RPN
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Anchor Box
Predefined boxes of various sizes and ratios serving as references for object detection.
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6 stops · basics first
- Machine Learning ✓ understood
Building systems that learn patterns from data instead of following hand-written rules, getting better at a task as they see more examples.
- Neural Network ✓ understood
A computational model inspired by biological neural networks, consisting of interconnected nodes (neurons) organized in layers that process information through weighted connections.
- Deep Learning ✓ understood
A subset of machine learning that uses neural networks with multiple layers (deep neural networks) to learn hierarchical representations of data.
- Computer Vision ✓ understood
The field of AI that gets computers to extract meaning from images and video: what is in them, where it is, and how it moves.
- Bounding Box ✓ understood
A rectangular box defined by coordinates that localizes an object in an image, used in object detection.
- Object Detection ✓ understood
Finding every object of interest in an image and giving each a class label, a confidence score and a bounding box.
- Anchor Box · you are here ✓ understood
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Vision & Multimodal Region Proposal Network A network generating candidate object locations for two-stage detectors like Faster R-CNN. Vision & Multimodal Faster R-CNN An object detection architecture with RPN for efficient region proposals. Vision & Multimodal YOLO You Only Look Once - a real-time object detection architecture treating detection as regression. Vision & Multimodal RetinaNet A single-stage object detector using focal loss to handle class imbalance.