Liyuan Liu
Researcher / author (OpenAlex)
Facts
2 properties- Affiliation
- Southwest University, Chinese Academy of Sciences, Institute of Semiconductors, Saint Joseph's Universityas of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 2
- ORCID iD
- 0000-0003-2585-323X
- OpenAlex ID
- A5100657035, A5128830220, A5137582186as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 52
3-D Deployment of UAV-BSs for Effective Communication Coverage,
A 0.9–2.25-GHz Sub-0.2-mW/GHz Compact Low-Voltage Low-Power Hybrid Digital PLL With Loop Bandwidth-Tracking Technique,
A2Text-Net: A Novel Deep Neural Network for Sarcasm Detection,
A 64 × 128 3D-Stacked SPAD Image Sensor for Low-Light Imaging,
A Bio-Inspired Spiking Vision Chip Based on SPAD Imaging and Direct Spike Computing for Versatile Edge Vision,
Abnormal Activity Detection in Edge Computing: A Transfer Learning Approach,
A Compact High-Quality Image Demosaicking Neural Network for Edge-Computing Devices,
A Cost-Efficient High-Speed VLSI Architecture for Spiking Convolutional Neural Network Inference Using Time-Step Binary Spike Maps
+44 more
← Authored by 52
3-D Deployment of UAV-BSs for Effective Communication Coverage,
A 0.9–2.25-GHz Sub-0.2-mW/GHz Compact Low-Voltage Low-Power Hybrid Digital PLL With Loop Bandwidth-Tracking Technique,
A2Text-Net: A Novel Deep Neural Network for Sarcasm Detection,
A 64 × 128 3D-Stacked SPAD Image Sensor for Low-Light Imaging,
A Bio-Inspired Spiking Vision Chip Based on SPAD Imaging and Direct Spike Computing for Versatile Edge Vision,
Abnormal Activity Detection in Edge Computing: A Transfer Learning Approach,
A Compact High-Quality Image Demosaicking Neural Network for Edge-Computing Devices,
A Cost-Efficient High-Speed VLSI Architecture for Spiking Convolutional Neural Network Inference Using Time-Step Binary Spike Maps
+44 more
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Summary
Liyuan Liu is a human[1].