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Ponencia
Event-based Row-by-Row Multi-convolution engine for Dynamic-Vision Feature Extraction on FPGA
(IEEE Computer Society, 2018)
Neural networks algorithms are commonly used to recognize patterns from different data sources such as audio or vision. In image recognition, Convolutional Neural Networks are one of the most effective techniques due ...
Ponencia
Spiking row-by-row FPGA Multi-kernel and Multi-layer Convolution Processor.
(IEEE Computer Society, 2019)
Spiking convolutional neural networks have become a novel approach for machine vision tasks, due to the latency to process an input stimulus from a scene, and the low power consumption of these kind of solutions. ...
Artículo
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps
(IEEE Computer Society, 2019)
Convolutional neural networks (CNNs) have become the dominant neural network architecture for solving many stateof- the-art (SOA) visual processing tasks. Even though Graphical Processing Units (GPUs) are most often ...
Artículo
Neuromorphic LIF Row-by-Row Multiconvolution Processor for FPGA
(IEEE Computer Society, 2018)
Deep Learning algorithms have become state-of-theart methods for multiple fields, including computer vision, speech recognition, natural language processing, and audio recognition, among others. In image vision, ...