VLSI Layout Hotspot Detection Based on DiscriminativeFeature Extraction
論文筆記–VLSI Layout Hotspot Detection Based on DiscriminativeFeature Extraction 基於鑑別特徵提取的超大規模集成電路版圖熱點檢測 摘要 特徵提取是基於機器學習的VLSI佈局熱點檢測流程的關鍵階段。 常規的基於機器學習的方法應用各種特徵提取技術來近似納米級的原始佈局結構。 但是，在近似過程中會丟失一些重要的佈局模式信息，從而導致
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相關文章
- 1. 《BUILDING CHANGE DETECTION BASED ON 3D RECONSTRUCTION》
- 2. Detection簡記1-Vehicles Detection Based on Background Modeling
- 3. Summary of defect detection algorithms based on deep learning
- 4. A Robust Hand Detection Method Based on Skin Probability Map
- 5. A Surface Defect Detection Method Based on Positive Samples
- 6. Healthcare Fraud Detection Based on Trustworthiness of Doctors
- 7. Visual saliency detection based on multiscale deep cnn features
- 8. Automatic Ship Detection in Optical Remote Sensing Images Based on Anomaly Detection and SPP-PCANet
- 9. Machine Learning-based Web Exception Detection
- 10. Joint Extraction of Entities and Relations Based on a Novel Decomposition Strategy (ECAI2020)