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Deta Swin Large O365
DETA is a transformer-based object detection model that significantly improves training efficiency and detection performance by reintroducing IoU assignment and non-maximum suppression techniques.
Downloads 73
Release Time : 1/30/2023
Model Overview
DETA is an innovative object detection model that combines transformer architecture with traditional IoU assignment and non-maximum suppression techniques, achieving fast convergence and high-precision detection.
Model Features
Fast convergence
Achieves 50.2 mAP on COCO dataset with only 12 training epochs
Efficient training
Training and testing speeds comparable to Deformable DETR
Innovative assignment mechanism
Reintroduces IoU assignment and non-maximum suppression techniques
Model Capabilities
Object detection
Image analysis
Object recognition
Use Cases
Computer vision
Smart surveillance
Used for real-time multi-object detection in surveillance videos
Efficiently and accurately identifies and tracks multiple objects
Autonomous driving
Used for object detection in road scenes
Quickly and accurately identifies vehicles, pedestrians, and traffic signs
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