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HAPPi-Net: Hardware-Aware Performant Perception of Neural Networks.. Technical University of Munich, Germany, (2021)Mind the Scaling Factors: Resilience Analysis of Quantized Adversarially Robust CNNs., , , , , , , and . DATE, page 706-711. IEEE, (2022)Adversarial Robust Model Compression Using In-Train Pruning., , , , , , , , , and 2 other author(s). CVPR Workshops, page 66-75. Computer Vision Foundation / IEEE, (2021)HW-Flow: A Multi-Abstraction Level HW-CNN Codesign Pruning Methodology., , , , , , , , , and . Leibniz Trans. Embed. Syst., 8 (1): 03:1-03:30 (2022)The ZuSE-KI-Mobil AI Accelerator SoC: Overview and a Functional Safety Perspective., , , , , , , , , and 8 other author(s). DATE, page 1-6. IEEE, (2023)Pruning CNNs for LiDAR-based Perception in Resource Constrained Environments., , , , , , , , and . IV Workshops, page 228-235. IEEE, (2021)Binary-LoRAX: Low-Latency Runtime Adaptable XNOR Classifier for Semi-Autonomous Grasping with Prosthetic Hands., , , , , , , , , and 2 other author(s). ICRA, page 13430-13437. IEEE, (2021)WinoTrain: Winograd-Aware Training for Accurate Full 8-bit Convolution Acceleration., , , , , , , and . DAC, page 1-6. IEEE, (2023)OrthrusPE: Runtime Reconfigurable Processing Elements for Binary Neural Networks., , , and . DATE, page 1662-1667. IEEE, (2020)Binary DAD-Net: Binarized Driveable Area Detection Network for Autonomous Driving., , , , , , and . ICRA, page 2295-2301. IEEE, (2020)