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https://www.academia.edu/13532661/A_Hardware-friendly_Support_Vector_Machine_for_Embedded_Automotive_Applications
A Hardware-friendly Support Vector Machine for Embedded Automotive Applications
https://link.springer.com/chapter/10.1007/978-3-642-35395-6_30
A hardware-friendly support vector machine for embedded automotive applications. In: International Joint Conference on Neural Networks, IJCNN 2007, pp. 1360–1364 (August 2007) Google Scholar 14.Cited by: 582
https://link.springer.com/article/10.1007/s10766-017-0514-1
Jun 23, 2017 · Support Vector Machines (SVMs) are considered as a state-of-the-art classification algorithm capable of high accuracy rates for a different range of applications. When arranged in a cascade... Boosting the Hardware-Efficiency of Cascade Support Vector Machines for Embedded Classification Applications SpringerLinkAuthor: Christos Kyrkou, Theocharis Theocharides, Christos-Savvas Bouganis, Marios M. Polycarpou
https://core.ac.uk/display/54751400
Abstract. We present here a hardware-friendly version of the support vector machine (SVM), which is useful to implement its feed-forward phase on limited-resources devices such as field programmable gate arrays (FPGAs) or microcontrollers, where a floating-point unit is seldom available.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.4826
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): ABSTRACT: A hardware-friendly version of the well-known Support Vector Machine (SVM) is presented in this work, useful to implement its feed-forward phase on resource-limited architectures, such as Field Programmable Gate Arrays (FPGAs) or microcontrollers. In many embedded applications, a floating …
https://www.sciencedirect.com/science/article/pii/S1877050911001116
Effects of Reduced Precision on Floating-Point SVM Classification Accuracy. ... Anguita, A. Ghio, S. Pischiutta, S. Ridella, A hardware-friendly support vector machine for embedded automotive applications, in: Neural Networks, 2007. ... S. Pischiutta, S. Ridella, A hardware-friendly support vector machine for embedded automotive applications ...Cited by: 19
https://www.embedded.com/applying-machine-learning-in-embedded-systems/
Jul 11, 2018 · Machine learning has evolved rapidly from an interesting research topic to an effective solution for a wide range of applications. Its apparent effectiveness has rapidly accelerated interest from a growing developer base well outside the community of AI theoreticians.
http://core.ac.uk/display/21031582
Abstract. ABSTRACT: A hardware-friendly version of the well-known Support Vector Machine (SVM) is presented in this work, useful to implement its feed-forward phase on resource-limited architectures, such as Field Programmable Gate Arrays (FPGAs) or microcontrollers.
https://github.com/jonnor/embeddedml/
A Hardware-friendly Support Vector Machine for Embedded Automotive Applications. Used down to 12 bit without significant reduction in performance. Approximate RBF Kernel SVM and Its Applications in Pedestrian Classification. Paper presents an O(d*(d+3)/2) implementation to the nonlinear RBF-kernel SVM by employing the second-order polynomial ...
https://www.worldscientific.com/doi/abs/10.1142/S0218126611007244
A FPGA CORE GENERATOR FOR EMBEDDED CLASSIFICATION SYSTEMS ... Using variable neighborhood search to improve the support vector machine performance in embedded automotive applications, IEEE Int. Joint Conf. Neural Networks (2008) pp. 984–988. Google Scholar; D. Anguita et al., A hardware-friendly support vector machine for embedded automotive ...Cited by: 26
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