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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., , , , , , , и . DATE, стр. 706-711. IEEE, (2022)Adversarial Robust Model Compression Using In-Train Pruning., , , , , , , , , и 2 other автор(ы). CVPR Workshops, стр. 66-75. Computer Vision Foundation / IEEE, (2021)Binary-LoRAX: Low-Latency Runtime Adaptable XNOR Classifier for Semi-Autonomous Grasping with Prosthetic Hands., , , , , , , , , и 2 other автор(ы). ICRA, стр. 13430-13437. IEEE, (2021)Pruning CNNs for LiDAR-based Perception in Resource Constrained Environments., , , , , , , , и . IV Workshops, стр. 228-235. IEEE, (2021)The ZuSE-KI-Mobil AI Accelerator SoC: Overview and a Functional Safety Perspective., , , , , , , , , и 8 other автор(ы). DATE, стр. 1-6. IEEE, (2023)HW-Flow: A Multi-Abstraction Level HW-CNN Codesign Pruning Methodology., , , , , , , , , и . Leibniz Trans. Embed. Syst., 8 (1): 03:1-03:30 (2022)WinoTrain: Winograd-Aware Training for Accurate Full 8-bit Convolution Acceleration., , , , , , , и . DAC, стр. 1-6. IEEE, (2023)BinaryCoP: Binary Neural Network-based COVID-19 Face-Mask Wear and Positioning Predictor on Edge Devices., , , , , и . IPDPS Workshops, стр. 108-115. IEEE, (2021)DSC: Dense-Sparse Convolution for Vectorized Inference of Convolutional Neural Networks., , , , и . CVPR Workshops, стр. 1353-1360. Computer Vision Foundation / IEEE, (2019)