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RE-Specter: Examining the Architectural Features of Configurable CNN With Power Side-Channel., , , , , , , , , и 1 other автор(ы). IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 43 (10): 2916-2929 (октября 2024)An N-way group association architecture and sparse data group association load balancing algorithm for sparse CNN accelerators., , , , и . ASP-DAC, стр. 329-334. ACM, (2019)14.2 A 65nm 24.7µJ/Frame 12.3mW Activation-Similarity-Aware Convolutional Neural Network Video Processor Using Hybrid Precision, Inter-Frame Data Reuse and Mixed-Bit-Width Difference-Frame Data Codec., , , , , , , , , и . ISSCC, стр. 232-234. IEEE, (2020)A new feature extraction algorithm for measuring the spatial arrangement of texture Primitives: Distance coding diversity., , , и . Int. J. Appl. Earth Obs. Geoinformation, (2024)A Dynamic Execution Neural Network Processor for Fine-Grained Mixed-Precision Model Training Based on Online Quantization Sensitivity Analysis., , , , , , и . IEEE J. Solid State Circuits, 59 (9): 3082-3093 (сентября 2024)Toward Low-Bit Neural Network Training Accelerator by Dynamic Group Accumulation., , , , , и . ASP-DAC, стр. 442-447. IEEE, (2022)A 28nm 1.07TFLOPS/mm2 Dynamic-Precision Training Processor with Online Dynamic Execution and Multi- Level-Aligned Block-FP Processing., , , , , , , и . CICC, стр. 1-2. IEEE, (2023)A 65nm 0.39-to-140.3TOPS/W 1-to-12b Unified Neural Network Processor Using Block-Circulant-Enabled Transpose-Domain Acceleration with 8.1 × Higher TOPS/mm2and 6T HBST-TRAM-Based 2D Data-Reuse Architecture., , , , , , , , , и 3 other автор(ы). ISSCC, стр. 138-140. IEEE, (2019)Block-Wise Dynamic-Precision Neural Network Training Acceleration via Online Quantization Sensitivity Analytics., , , , , и . ASP-DAC, стр. 372-377. ACM, (2023)PETRI: Reducing Bandwidth Requirement in Smart Surveillance by Edge-Cloud Collaborative Adaptive Frame Clustering and Pipelined Bidirectional Tracking., , , , и . DAC, стр. 421-426. IEEE, (2021)