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Impact of temporal subsampling on accuracy and performance in practical video classification., , , , , и . EUSIPCO, стр. 996-1000. IEEE, (2017)Going Further With Winograd Convolutions: Tap-Wise Quantization for Efficient Inference on 4x4 Tile., , , , и . CoRR, (2022)CUTIE: Beyond PetaOp/s/W Ternary DNN Inference Acceleration With Better-Than-Binary Energy Efficiency., , , и . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 41 (4): 1020-1033 (2022)Design Automation for Binarized Neural Networks: A Quantum Leap Opportunity?, , и . ISCAS, стр. 1-5. IEEE, (2018)Towards Edge-Aware Spatio-Temporal Filtering in Real-Time., , , , , и . IEEE Trans. Image Process., 27 (1): 265-280 (2018)InfiniWolf: Energy Efficient Smart Bracelet for Edge Computing with Dual Source Energy Harvesting., , , , и . DATE, стр. 342-345. IEEE, (2020)FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things., , , и . IEEE Internet Things J., 7 (5): 4403-4417 (2020)Extended Bit-Plane Compression for Convolutional Neural Network Accelerators., и . CoRR, (2018)Hydra: An Accelerator for Real-Time Edge-Aware Permeability Filtering in 65nm CMOS., , , , , , и . ISCAS, стр. 1-5. IEEE, (2018)Hydra: An Accelerator for Real-Time Edge-Aware Permeability Filtering in 65nm CMOS., , , , , , и . CoRR, (2017)