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Artículo
Comprehensive Evaluation of OpenCL-based Convolutional Neural Network Accelerators in Xilinx and Altera FPGAs
(Cornell University, 2016)
Deep learning has significantly advanced the state of the art in artificial intelligence, gaining wide popularity from both industry and academia. Special interest is around Convolutional Neural Networks (CNN), which take ...
Ponencia
Comprehensive Evaluation of OpenCL-Based CNN Implementations for FPGAs
(Springer, 2017)
Deep learning has significantly advanced the state of the art in artificial intelligence, gaining wide popularity from both industry and academia. Special interest is around Convolutional Neural Networks (CNN), which ...
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 ...
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 ...