FPGA based implementation of convolutional neural network for hyperspectral classification

Xiaofeng Chen; Jingyu Ji; Shaohui Mei; Yifan Zhang; Manli Han; Qian Du

doi:10.1109/IGARSS.2018.8517973

FPGA based implementation of convolutional neural network for hyperspectral classification

Xiaofeng Chen, Jingyu Ji, Shaohui Mei, Yifan Zhang, Manli Han, Qian Du

School of Electronics and Information

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

convolutional neural network (CNN) has been widely used for hyperspectral classification. Current researches of CNN based hyperspectral image classification is mainly implemented on graphics processing unit (GPU) platform. However, GPU is not suitable for onboard processing due to the problem of space radiation and power supply on image acquiring platform. Therefore, in this paper, FPGA is selected to implement CNN based hyperspectral classification for further onboard processing. Specially, a hardware model is designed for the forward classification step of CNN using hardware description language, including computation structure for CNN, implementation of different layers, weight loading scheme, and data interfere. Simulation results over Pavia data set validate the proposed FPGA based implementation is coincide with that on GPU platform.

Original language	English
Title of host publication	2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2451-2454
Number of pages	4
ISBN (Electronic)	9781538671504
DOIs	https://doi.org/10.1109/IGARSS.2018.8517973
State	Published - 31 Oct 2018
Event	38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Valencia, Spain Duration: 22 Jul 2018 → 27 Jul 2018

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2018-July

Conference

Conference	38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Country/Territory	Spain
City	Valencia
Period	22/07/18 → 27/07/18

Keywords

Classification
Convolutional neural network
FPGA
Hyperspectral

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10.1109/IGARSS.2018.8517973

Cite this

Chen, X., Ji, J., Mei, S., Zhang, Y., Han, M., & Du, Q. (2018). FPGA based implementation of convolutional neural network for hyperspectral classification. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings (pp. 2451-2454). Article 8517973 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2018.8517973

Chen, Xiaofeng ; Ji, Jingyu ; Mei, Shaohui et al. / FPGA based implementation of convolutional neural network for hyperspectral classification. 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 2451-2454 (International Geoscience and Remote Sensing Symposium (IGARSS)).

@inproceedings{c2d12b27876f4a7aba8be59b27c15d41,

title = "FPGA based implementation of convolutional neural network for hyperspectral classification",

abstract = "convolutional neural network (CNN) has been widely used for hyperspectral classification. Current researches of CNN based hyperspectral image classification is mainly implemented on graphics processing unit (GPU) platform. However, GPU is not suitable for onboard processing due to the problem of space radiation and power supply on image acquiring platform. Therefore, in this paper, FPGA is selected to implement CNN based hyperspectral classification for further onboard processing. Specially, a hardware model is designed for the forward classification step of CNN using hardware description language, including computation structure for CNN, implementation of different layers, weight loading scheme, and data interfere. Simulation results over Pavia data set validate the proposed FPGA based implementation is coincide with that on GPU platform.",

keywords = "Classification, Convolutional neural network, FPGA, Hyperspectral",

author = "Xiaofeng Chen and Jingyu Ji and Shaohui Mei and Yifan Zhang and Manli Han and Qian Du",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE; 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 ; Conference date: 22-07-2018 Through 27-07-2018",

year = "2018",

month = oct,

day = "31",

doi = "10.1109/IGARSS.2018.8517973",

language = "英语",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2451--2454",

booktitle = "2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings",

}

Chen, X, Ji, J, Mei, S, Zhang, Y, Han, M & Du, Q 2018, FPGA based implementation of convolutional neural network for hyperspectral classification. in 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings., 8517973, International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2018-July, Institute of Electrical and Electronics Engineers Inc., pp. 2451-2454, 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, 22/07/18. https://doi.org/10.1109/IGARSS.2018.8517973

FPGA based implementation of convolutional neural network for hyperspectral classification. / Chen, Xiaofeng; Ji, Jingyu; Mei, Shaohui et al.
2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 2451-2454 8517973 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - FPGA based implementation of convolutional neural network for hyperspectral classification

AU - Chen, Xiaofeng

AU - Ji, Jingyu

AU - Mei, Shaohui

AU - Zhang, Yifan

AU - Han, Manli

AU - Du, Qian

PY - 2018/10/31

Y1 - 2018/10/31

N2 - convolutional neural network (CNN) has been widely used for hyperspectral classification. Current researches of CNN based hyperspectral image classification is mainly implemented on graphics processing unit (GPU) platform. However, GPU is not suitable for onboard processing due to the problem of space radiation and power supply on image acquiring platform. Therefore, in this paper, FPGA is selected to implement CNN based hyperspectral classification for further onboard processing. Specially, a hardware model is designed for the forward classification step of CNN using hardware description language, including computation structure for CNN, implementation of different layers, weight loading scheme, and data interfere. Simulation results over Pavia data set validate the proposed FPGA based implementation is coincide with that on GPU platform.

AB - convolutional neural network (CNN) has been widely used for hyperspectral classification. Current researches of CNN based hyperspectral image classification is mainly implemented on graphics processing unit (GPU) platform. However, GPU is not suitable for onboard processing due to the problem of space radiation and power supply on image acquiring platform. Therefore, in this paper, FPGA is selected to implement CNN based hyperspectral classification for further onboard processing. Specially, a hardware model is designed for the forward classification step of CNN using hardware description language, including computation structure for CNN, implementation of different layers, weight loading scheme, and data interfere. Simulation results over Pavia data set validate the proposed FPGA based implementation is coincide with that on GPU platform.

KW - Classification

KW - Convolutional neural network

KW - FPGA

KW - Hyperspectral

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Chen X, Ji J, Mei S, Zhang Y, Han M, Du Q. FPGA based implementation of convolutional neural network for hyperspectral classification. In 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 2451-2454. 8517973. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS.2018.8517973

FPGA based implementation of convolutional neural network for hyperspectral classification

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