Classification of road side material using convolutional neural network and a proposed implementation of the network through Zedboard Zynq 7000 FPGA

Classification of road side material using convolutional neural network and a proposed implementation of the network through Zedboard Zynq 7000 FPGA

Indiana University-Purdue University Indianapolis (IUPUI) === In recent years, Convolutional Neural Networks (CNNs) have become the state-of- the-art method for object detection and classi cation in the eld of machine learning and arti cial intelligence. In contrast to a fully connected network,...

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Bibliographic Details
Main Author: Rahman, Tanvir
Other Authors: Christopher, Lauren
Language:en_US
Published: 2018
Subjects:
Convolutional Neural Net
Field Programmable Gate Array
Transfer Learninig
Self Organizing Maps
High Level Synthesis
CIFAR-10
Classification
ZedBoard
Online Access:http://hdl.handle.net/1805/15113
https://doi.org/10.7912/C24Q0X

Internet

http://hdl.handle.net/1805/15113
https://doi.org/10.7912/C24Q0X

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