VLSI Layout Hotspot Detection Based on DiscriminativeFeature Extraction
论文笔记–VLSI Layout Hotspot Detection Based on DiscriminativeFeature Extraction 基于鉴别特征提取的超大规模集成电路版图热点检测 摘要 特征提取是基于机器学习的VLSI布局热点检测流程的关键阶段。 常规的基于机器学习的方法应用各种特征提取技术来近似纳米级的原始布局结构。 但是，在近似过程中会丢失一些重要的布局模式信息，从而导致
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相关文章
- 1. 《BUILDING CHANGE DETECTION BASED ON 3D RECONSTRUCTION》
- 2. Detection简记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)