FPGA-based Hardware Acceleration for SVM Machine Learning Algorithm

Jakjoud Fatimazahra; Hatim Anas; Abella Bouaaddi

doi:10.1051/e3sconf/202122901024

All issues

Volume 229 (2021)

E3S Web Conf., 229 (2021) 01024

References

Open Access

Issue		E3S Web Conf. Volume 229, 2021 The 3^rd International Conference of Computer Science and Renewable Energies (ICCSRE’2020)


Article Number		01024
Number of page(s)		4
DOI		https://doi.org/10.1051/e3sconf/202122901024
Published online		25 January 2021

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[1] Rong Xie, Xiaoqin Feng, A method of quick edge detection based on Zynq, 3^rd international conference on cloud computing and internet of thing, IEEE, (2018) [Google Scholar]

[2] Georgios Tzanos, Christoforos Kachris, Dimitrios Soudris, Hardware Acceleration on Gaussian Naive Bayes machine learning algorithm, international on modern circuits and systems technologies, (2019) [Google Scholar]

[3] P. Chaudhary and M.K. Sharma, VLSI Hardware Architecture of Real time Pattern Classification using Nave Bayed Classifier, in Proceedings of the 2017 2^nd International Conference on Multimedia Systems and Signal ProcessingICMSSP 2017 [Google Scholar]

[4] Luca Stornaiuolo, Marco D, Donatella Sciuto, On how to efficiently implement Deep Learning algorithms on PYNQ platform, Computer Society annual symposium on VLSI, IEEE, 2018 [Google Scholar]

[5] “Bnn-pynq, ” https://github.com/Xilinx/BNNPYNQ/. [Google Scholar]

[6] C, Zhang, P. Li, G. Sun, Y. Guan, B. Xiao, J. Cong, « Optimizing fpga-based accelerator design for deeo convolutional neural networks », in Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, ACM, 2015, pp.161-170 [Google Scholar]

[7] Wei Zhou, Ling Zhang, Xin Lou, Histogram of Oriented Gradients Feature Extraction From Raw Bayer Pattern Images, IEEE Transactions on circuits and systems – II: Express Briefs, Vol. 67, No 5, May 2020 [Google Scholar]

[8] Harihara Santosh Dadi, Gopala Krishna Mohan Pillutla, Improved Face Recognition Rate Using HOG Features and SVM Classifier, Journal of Electronics and Communication Engineering, ISSN:2278-8735, Volume 11, Issue 4, Ver. I, Jul Aug 2016, pp 34-44 [Google Scholar]

[9] Samy Bakheet, An SVM Framework for Malignant Melanoma Detection Based on Optimized HOG Features, Computation 2017, 5, 4 [Google Scholar]