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- W2783304105 abstract "Human or pedestrian detection is an attractive headline and has been proposed in computer vision and machine learning fields. Real time detection and low power system is a critical challenges. Support Vector Machine algorithm with Histograms of oriented gradients (HOG) feature descriptor is given a high successful result, fast and reliable, for human detection. Therefore, this paper demonstrates how to implement HOG feature descriptor with Support Vector Machine (SVM) using FPGA and presents a report that includes FPGA's resource utilization, time consuming, power consumption and SVM accuracy results." @default.
- W2783304105 created "2018-01-26" @default.
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- W2783304105 date "2017-11-01" @default.
- W2783304105 modified "2023-10-03" @default.
- W2783304105 title "The implementation of Support Vector Machine (SVM) using FPGA for human detection" @default.
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