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Mostrando ítems 1-10 de 11
Ponencia
Work-in-Progress: A Neuromorphic Approach of the Sound Source Localization Task in Real-Time Embedded Systems
(ACM Digital Library, 2019)
Autonomous robots have become a very popular topic within the artificial intelligence field. These systems are able to perform difficult or risky tasks that could be dangerous when done by humans or trained animals. ...
Artículo
Efficient Memory Organization for DNN Hardware Accelerator Implementation on PSoC
(MDPI, 2021-01)
The use of deep learning solutions in different disciplines is increasing and their algorithms are computationally expensive in most cases. For this reason, numerous hardware accelerators have appeared to compute their ...
Ponencia
Live Demonstration: Neuromorphic Row-by-Row Multi-convolution FPGA Processor-SpiNNaker architecture for Dynamic-Vision Feature Extraction
(IEEE Computer Society, 2019)
In this demonstration a spiking neural network architecture for vision recognition using an FPGA spiking convolution processor, based on leaky integrate and fire neurons (LIF) and a SpiNNaker board is presented. The ...
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 ...
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 ...
Ponencia
A 20Mevps/32Mev event-based USB framework for neuromorphic systems debugging
(IEEE Computer Society, 2016)
Neuromorphic systems are engineering solutions that take inspiration from biological neural systems. They use spike-or event-based representation and codification of the information. This codification allows performing ...
Ponencia
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
(ACM Digital Library, 2019)
This demonstration shows a Dynamic Vision Sensor able to capture visual motion at a speed equivalent to a highspeed camera (20k fps). The collected visual information is presented as normalized histogram to a CNN ...