<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "An Adaptive Hardware Architecture using Quantized HOG Features for Object Detection"^^ . "This article presents an adaptive hardware architecture for high-performance object detection using Histogram of Oriented Gradient (HOG) features in combination with Supported Vector Machines (SVM). This architecture can adapt to various bit-width representations of HOG features by using the quantization technique. The HOG features can be represented from 8 bits to 4 bits to remove the bubble in the processing pipeline and reduce the memory footprint. As a result, the overall throughput is robustly increased as the number of bits decreases. Moreover, we propose a new cell-reused strategy to speed up the system throughput and reduce memory footprint. The proposed architecture has been implemented in TSMC 65nm technology with a maximum operating frequency of 500MHz and throughput of 3.98Gbps. The total hardware area cost is about 167KGEs and 212kb SRAMs. © 2022 IEEE."^^ . "2022" . . . "Institute of Electrical and Electronics Engineers Inc."^^ . . "Institute of Electrical and Electronics Engineers Inc."^^ . . . "Proceedings of 2022 IEEE International Conference on IC Design and Technology, ICICDT 2022"^^ . . . . . . . . . . . . . . . . . "X.-T."^^ . "Tran"^^ . "X.-T. Tran"^^ . . "D.-H."^^ . "Bui"^^ . "D.-H. Bui"^^ . . "F.A."^^ . "Hussin"^^ . "F.A. Hussin"^^ . . "N.-D."^^ . "Nguyen"^^ . "N.-D. Nguyen"^^ . . . . . "HTML Summary of #17374 \n\nAn Adaptive Hardware Architecture using Quantized HOG Features for Object Detection\n\n" . "text/html" . .