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Energy Consumption - Quantization
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Classroom Contents
TinyML Talks Germany - Neural Network Framework Using Emerging Technologies for Screening Diabetic
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- 1 Intro
- 2 Diabetic Retinopathy(DR)
- 3 Convolutional Neural Networks CN
- 4 Related Work - CNN Literature
- 5 Computation in memory (CIM) Architecture
- 6 Resistive Random Access Memory RE
- 7 Tasks in this work
- 8 Performance Metrics
- 9 Data Processing
- 10 Model Training
- 11 Severity Label (SL)
- 12 Model Compression
- 13 Multi-class accuracy
- 14 Severity Label Accuracy
- 15 Model Evaluation
- 16 Compression Schemes
- 17 Latency
- 18 Energy Consumption - Quantization
- 19 Conclusion
- 20 High-Value or Safety-Critical Use Cases? For your most important projects, use
- 21 Renesas is enabling the next generation of Al-powered solutions that will revolutionise every industry sector
- 22 Silver Strategic Partners
