Pinned Repositories
cs217.github.io
Course Webpage for CS 217 Hardware Accelerators for Machine Learning, Stanford University
design_pattern_sv
learning design pattern using system verilog
NPU_on_FPGA
在FPGA上面实现一个NPU计算单元。能够执行矩阵运算（ADD/ADDi/ADDs/MULT/MULTi/DOT等）、图像处理运算（CONV/POOL等）、非线性映射（RELU/TANH/SIGM等）。
posture_recognition_CNN
To help machines learn what we human beings are doing via a camera is important. Once it comes true, machines can make different responses to all kinds of human's postures. But the process is very difficult as well, because usually it is very slow and power-consuming, and requires a very large memory space. Here we focus on real-time posture recognition, and try to make the machine "know" what posture we make. The posture recognition system is consisted of DE10-Nano SoC FPGA Kit, a camera, and an HDMI monitor. SoC FPGA captures video streams from the camera, recognizes human postures with a CNN model, and finally shows the original video and classification result (standing, walking, waving, etc.) via HDMI interface.
cxdzyq1110's Repositories
cxdzyq1110/NPU_on_FPGA
在FPGA上面实现一个NPU计算单元。能够执行矩阵运算（ADD/ADDi/ADDs/MULT/MULTi/DOT等）、图像处理运算（CONV/POOL等）、非线性映射（RELU/TANH/SIGM等）。
cxdzyq1110/posture_recognition_CNN
To help machines learn what we human beings are doing via a camera is important. Once it comes true, machines can make different responses to all kinds of human's postures. But the process is very difficult as well, because usually it is very slow and power-consuming, and requires a very large memory space. Here we focus on real-time posture recognition, and try to make the machine "know" what posture we make. The posture recognition system is consisted of DE10-Nano SoC FPGA Kit, a camera, and an HDMI monitor. SoC FPGA captures video streams from the camera, recognizes human postures with a CNN model, and finally shows the original video and classification result (standing, walking, waving, etc.) via HDMI interface.
cxdzyq1110/design_pattern_sv
learning design pattern using system verilog
cxdzyq1110/cs217.github.io
Course Webpage for CS 217 Hardware Accelerators for Machine Learning, Stanford University