Sung. "FPGA based implementation of deep neural networks using on-chip memory only", IEEE International Conference Acoustics, Speech and Signal Processing (ICASSP), pp. 1011-1015, 2016.J. Park and W. Sung, "Fpga
Therefore, the implementation of CNN-based target detection algorithm accelerator using FPGA has become a hot research topic. For example, in 2016, Chen et al. designed a SIMD convolutional neural network acceleration system based on FPGA, which reduced the gap between the theoretical and actual ...
2021.AARRESTAD T, LONCAR V, GHIELMETTI N, et al. Fast convolutional neural networks on FPGAs wi...
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In this paper an FPGA-based implementation of a sequential discrete time cellular neural network (DT-CNN) with 3×3 templates is described. The architecture is based on a single pipelined cell which is employed to emulate a CNN with larger number of neurons. This solution diminishes the use ...
To explore a reasonable implementation of the spiking neural networks, a novel method is proposed in which the network topology is simulated by the software simulation libraries, and the key computations are handed over to the FPGA forparallel computing to meet the requirements of easydevelopment, ...
In this work, Convolutional Neural Network (CNN) is applied for defect identification of Swiven Cap (one type of medical component) based on Field-Programmable Gate Array (FPGA) implementation. Caffe is used as the platform to develop the CNN model. After training phase, a confusion matrix is...
An FPGA-based implementation of CNN hardware accelerator Qiu Zhenbo College of Photoelectric Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaAbstract: This paper proposes a general CNN hardware accelerator design scheme based on FPGA. For the most computationally ...