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A 20Mevps/32Mev event-based USB framework for neuromorphic systems debugging., , , , , and . EBCCSP, page 1-6. IEEE, (2016)Event-based Row-by-Row Multi-convolution engine for Dynamic-Vision Feature Extraction on FPGA., , , , , , and . IJCNN, page 1-7. IEEE, (2018)Performance evaluation over HW/SW co-design SoC memory transfers for a CNN accelerator., , , , , and . CoRR, (2018)Performance Evaluation of Neural Networks for Animal Behaviors Classification: Horse Gaits Case Study., , , , , , and . DCAI, volume 474 of Advances in Intelligent Systems and Computing, page 377-385. Springer, (2016)NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps., , , , , , , , , and 1 other author(s). IEEE Trans. Neural Networks Learn. Syst., 30 (3): 644-656 (2019)Efficient DMA transfers management on embedded Linux PSoC for Deep-Learning gestures recognition: Using Dynamic Vision Sensor and NullHop one-layer CNN accelerator to play RoShamBo., , , and . Interacción, page 59:1-59:2. ACM, (2019)Comprehensive Evaluation of OpenCL-Based CNN Implementations for FPGAs., , , , , and . IWANN (2), volume 10306 of Lecture Notes in Computer Science, page 271-282. Springer, (2017)Dynamic Vision Sensor integration on FPGA-based CNN accelerators for high-speed visual classification., , , , , and . ICONS, page 21:1-21:7. ACM, (2021)NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps, , , , , , , , , and 1 other author(s). (2017)cite arxiv:1706.01406.Accuracy Improvement of Neural Networks Through Self-Organizing-Maps over Training Datasets., , , , , , and . IWANN (1), volume 10305 of Lecture Notes in Computer Science, page 520-531. Springer, (2017)