Peter A. Beerel

202318 papers

1. ISPLEDBridging the Gap between Spiking Neural Networks & LSTMs for Latency & Energy Efficiency
2. DAC (T1)C2PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference
3. WACVEnabling ISP-less Low-Power Computer Vision
4. ICCV WorkshopFireFly: A Synthetic Dataset for Ember Detection in Wildfire
5. WACVFLOAT: Fast Learnable Once-for-All Adversarial Training for Tunable Trade-off between Accuracy and Robustness
6. ICASSP (T1)In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision
7. GLSVLSIIsland-based Random Dynamic Voltage Scaling vs ML-Enhanced Power Side-Channel Attacks
8. ICLR (T1)Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference
9. CVPR WorkshopMaking Models Shallow Again: Jointly Learning to Reduce Non-Linearity and Depth for Latency-Efficient Private Inference
10. Frontiers in NeuroinformaticsNeuromorphic-P2M: Processing-in-Pixel-in-Memory Paradigm for Neuromorphic Image Sensors
11. IEEE Trans on CADOn the Security of Sequential Logic Locking Against Oracle-Guided Attacks
12. ICASSP (T1)Quantpipe: Applying Adaptive Post-Training Quantization For Distributed Transformer Pipelines In Dynamic Edge Environments