The year 2011 marked an important transition for FPGA high-level synthesis (HLS), as it
went from prototyping to deployment. A decade later, in this article, we assess the progress …

Convolutional neural network (CNN) based object detection algorithms are becoming
dominant in many application fields due to their superior accuracy advantage over …

Deploying deep learning models on embedded systems for computer vision tasks has been
challenging due to limited compute resources and strict energy budgets. The majority of …

On the road to making self-driving cars a reality, academic and industrial researchers are
working hard to continue to increase safety while meeting technical and regulatory …

Hardware-software co-design is the new trend for deep neural network and FPGA
accelerator development, which iteratively revises and tunes the full system. The bottleneck …

摘要针对YOLOv4 在焊缝X 射线探伤缺陷图中检测精度与召回率低的问题, 设计了YOLOv4-cs
算法. 该算法改进了YOLOv4 的卷积方式, 使得模型训练参数大大减小, 其次通过去除下采样及在 …

High speed data streaming has been highly demanded by mobile end users and millimetre-
wave (mm-wave) radio-over-fiber (RoF) optical communications have been studied to satisfy …

Reconfigurable processor-based acceleration of deep convolutional neural network (DCNN)
algorithms has emerged as a widely adopted technique, with particular attention on sparse …

While traditional HLS (High-Level Synthesis) converts “high-level” C-like programs into
hardware automatically, producing high-performance designs still requires hardware …

With rapidly developing high-speed wireless communications, the 60 GHz millimeter-wave
(mm-wave) frequency range has attracted extensive interests, and radio-over-fiber (RoF) …