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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)

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Dynamic Vision Sensor integration on FPGA-based CNN accelerators for high-speed visual classification., , , and . CoRR, (2019)Live Demonstration: Neuromorphic Row-by-Row Multi-Convolution FPGA Processor-SpiNNaker Architecture for Dynamic-Vision Feature Extraction., , , , , and . ISCAS, page 1. IEEE, (2019)A neuromorphic approach of the sound source localization task in real-time embedded systems: work-in-progress., , , , , and . EMSOFT Companion, page 10. ACM, (2019)Real-time motor rotation frequency detection with event-based visual and spike-based auditory AER sensory integration for FPGA., , , , , and . EBCCSP, page 1-6. IEEE, (2015)Live demonstration - Multilayer spiking neural network for audio samples classification using SpiNNaker., , , , , , , and . ISCAS, page 1. IEEE, (2017)EdgeDRNN: Enabling Low-latency Recurrent Neural Network Edge Inference., , , , and . AICAS, page 41-45. IEEE, (2020)NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps., , , , , , , , , and 1 other author(s). CoRR, (2017)Live demonstration: Retinal ganglion cell software and FPGA implementation for object detection and tracking., , , and . ISCAS, page 1445. IEEE, (2016)Approaching Retinal Ganglion Cell Modeling and FPGA Implementation for Robotics., , , , , and . Entropy, 20 (6): 475 (2018)Multilayer Spiking Neural Network for Audio Samples Classification Using SpiNNaker., , , , , , and . ICANN (1), volume 9886 of Lecture Notes in Computer Science, page 45-53. Springer, (2016)