May 9, 2020 · This paper presents an OpenCL-based high-throughput FPGA accelerator for the YOLOv2 object detection algorithm on Arria-10 GX1150 FPGA.
This paper presents an OpenCL-based high-throughput FPGA accelerator for the YOLOv2 object detection algorithm on Arria-10 GX1150 FPGA. The proposed hardware ...
A dedicated hardware accelerator for real-time acceleration of YOLOv2 ; Journal: Journal of Real-Time Image Processing, 2020, № 3, p. 481-492 ; Publisher: ...
Jul 3, 2020 · Our design can perform real-time object detection (frame rate >. 60 fps) on the video stream captured by a high-definition resolution camera. E.
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Nov 8, 2023 · In this paper, we propose a novel hardware-friendly NMS algorithm for FPGA accelerator design. Our proposed algorithm alleviates the performance bottleneck of ...
In recent years, dedicated hardware accelerators for the acceleration of the convolutional neural network (CNN) have been extensively studied.
We proposed a hardware-aware algorithm-level optimization flow for YOLOv2 network including pruning, clustering, layer fusion, and quanti- zation to overcome ...
Sep 4, 2023 · This work tackles the challenges of deploying state- of-the-art object detection models onto FPGA devices for ultra- low latency applications, ...
This paper proposes a low-power CNN accelerator for edge inference of RTC systems, where the computations are operated in a column-wise manner, ...
We propose a new high-definition object detection technology based on an AI inference scheme and its implementation.