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California State Polytechnic University – Pomona

1. Espinosa, Mark. Implementation of Convolutional Neural Networks in FPGA for Image Classification.

Degree: M.S.E.E, Department of Electrical and Computer Engineering, 2019, California State Polytechnic University – Pomona

Machine Learning and Deep Learning its sub discipline are gaining popularity quickly. Machine Learning algorithms have been successfully deployed in a variety of applications such as Natural Language Processing, Optical Character Recognition, and Speech Recognition. Deep Learning particularly is suited to Computer Vision and Image Recognition tasks. The Convolutional Neural Networks employed in Deep Learning Neural Networks train a set of weights and biases which with each layer of the network learn to recognize key features in an image. This work set out to develop a scalable and modular FPGA implementation for Convolutional Neural Networks. It was the objective of this work to attempt to develop a system which could be configured to run as many layers as desired and test it using a currently defined CNN configuration, AlexNet. This type of system would allow a developer to scale a design to fit any size of FPGA from the most inexpensive to the costliest cutting-edge chip on the market. The objective of this work was achieved, and all layers were accelerated including Convolution, Affine, ReLu, Max Pool, and Softmax layers. The performance of the design was assessed, and it was determined its maximum achievable performance was approximately 3 GFLOPS. Advisors/Committee Members: Aliyazicioglu, Zekeriya (advisor), Kang, James (committee member).

Subjects/Keywords: machine learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Espinosa, M. (2019). Implementation of Convolutional Neural Networks in FPGA for Image Classification. (Masters Thesis). California State Polytechnic University – Pomona. Retrieved from http://hdl.handle.net/10211.3/212122

Chicago Manual of Style (16th Edition):

Espinosa, Mark. “Implementation of Convolutional Neural Networks in FPGA for Image Classification.” 2019. Masters Thesis, California State Polytechnic University – Pomona. Accessed August 24, 2019. http://hdl.handle.net/10211.3/212122.

MLA Handbook (7th Edition):

Espinosa, Mark. “Implementation of Convolutional Neural Networks in FPGA for Image Classification.” 2019. Web. 24 Aug 2019.

Vancouver:

Espinosa M. Implementation of Convolutional Neural Networks in FPGA for Image Classification. [Internet] [Masters thesis]. California State Polytechnic University – Pomona; 2019. [cited 2019 Aug 24]. Available from: http://hdl.handle.net/10211.3/212122.

Council of Science Editors:

Espinosa M. Implementation of Convolutional Neural Networks in FPGA for Image Classification. [Masters Thesis]. California State Polytechnic University – Pomona; 2019. Available from: http://hdl.handle.net/10211.3/212122

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