-
ILMPQ: An Intra-Layer Multi-Precision Deep Neural Network Quantization framew...
ILMPQ: An Intra-Layer Multi-Precision Deep Neural Network Quantization framework for FPGA -
SceneScan Pro
Real-time stereo vision implementation on FPGAs with SceneScan Pro -
TransparentFPGAAccelerationwithTensorFlow
The dataset used in this paper is a collection of neural network acceleration with TensorFlow and FPGA. -
Intelligent Traffic Light Controller (I-TLC) system
The dataset used in this paper is a traffic light controller system designed using Verilog and implemented on a Field-Programmable Gate Array (FPGA). -
FPGA Implementation of Simpliļ¬ed Spiking Neural Network
The proposed model is validated on a Xilinx Virtex 6 FPGA and analyzes a fully connected network which consists of 800 neurons and 12,544 synapses in real-time. -
FPGA deep learning acceleration based on convolutional neural network
This paper proposes a convolutional neural network hardware accelerator based on field programmable logic gate array (FPGA). -
Caffe Framework with FPGA Support
The dataset used in this paper is a modified version of the Caffe CNN framework with support for FPGA implementations. -
FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters
The dataset used in this paper is a CNN training dataset, specifically VGG-16, VGG-19, and AlexNet.
