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Efficient memory compression in deep neural networks using coarse-grain sparsification for speech applications., , , и . ICCAD, стр. 78. ACM, (2016)A real-time 17-scale object detection accelerator with adaptive 2000-stage classification in 65nm CMOS., , , , , , , , и . ISCAS, стр. 1-4. IEEE, (2017)ECG Authentication Neural Network Hardware Design with Collective Optimization of Low Precision and Structured Compression., , , , , , и . ISCAS, стр. 1-5. IEEE, (2019)A 8.93-TOPS/W LSTM Recurrent Neural Network Accelerator Featuring Hierarchical Coarse-Grain Sparsity With All Parameters Stored On-Chip., , , и . ESSCIRC, стр. 119-122. IEEE, (2019)A Real-Time 17-Scale Object Detection Accelerator With Adaptive 2000-Stage Classification in 65 nm CMOS., , , , , , и . IEEE Trans. Circuits Syst. I Regul. Pap., 66-I (10): 3843-3853 (2019)Technology-design co-optimization of resistive cross-point array for accelerating learning algorithms on chip., , , , , , , , , и . DATE, стр. 854-859. ACM, (2015)Comprehensive Evaluation of OpenCL-Based CNN Implementations for FPGAs., , , , , и . IWANN (2), том 10306 из Lecture Notes in Computer Science, стр. 271-282. Springer, (2017)Compressing LSTM Networks with Hierarchical Coarse-Grain Sparsity., , , , и . INTERSPEECH, стр. 21-25. ISCA, (2020)A Smart Hardware Security Engine Combining Entropy Sources of ECG, HRV and SRAM PUF for Authentication and Secret Key Generation., , , , , и . A-SSCC, стр. 145-148. IEEE, (2019)On-Chip Learning and Inference Acceleration of Sparse Representations.. Arizona State University, Tempe, USA, (2019)base-search.net (ftarizonastateun:item:54867).