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Classroom Contents
Object Detection with Transformers - From Training to Deployment
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- 1 Introduction
- 2 Outline
- 3 Object Detection
- 4 Prediction Problem
- 5 Mean Average Precision
- 6 Why should we care
- 7 Transformer Decoder Architecture
- 8 Positional Encoding
- 9 Decoder
- 10 Prediction
- 11 Training
- 12 DebtR Performance
- 13 DebtR Drawbacks
- 14 Deformable Attention
- 15 Multiscale Features
- 16 Performance
- 17 State of the Art
- 18 Training Models
- 19 Defining PiTorch Trial
- 20 Defining Experiment Config
- 21 Determining Web UI
- 22 HP Search
- 23 Other Metrics
- 24 Tensorboard
- 25 Automatic Fault Tolerance
- 26 Save Model
- 27 Output
- 28 Results
- 29 Conclusion
