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Slides of "Machine Vision" course by Zhejiang University Smart Factory Innovation Club

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Vision2022

Slides of "Machine Vision" course by Zhejiang University Student Smart Factory Innovation Club

浙江大学学生智能工厂创新俱乐部《智能工厂软机器视觉教学》社团精品课程

Course Website: https://haodong-li.com/zju/tag/vision-2022/

Course Outline

  • Image basics: Pixels, Colors, Image formats
  • Image processing techniques: Filtering, Binarization, cutting, Morphological transformation, Scale and rotation transformation, Image gradient
  • Image pattern recognition: Line and circle detection, Feature point detection, Edge detection
  • Image pattern recognition: Blob detection, Feature point detection, Template matching
  • Neural Network basics: Neuron structure, Multi-layer Perceptron, Handwritten digit recognition, Loss function
  • Neural Network basics: Gradient Descent, Backpropagation
  • Modern Neural Network: Softmax regression, Deep neural network, Convolutional Neural Network, Server Resources
  • Modern Neural Network: Recurrent Neural Networks, Attention Mechanism & Transformer, Natural Language Processing, Reinforcement Learning, Generative Adversarial Networks
  • Final project and Q&A: Chess board recognition system

课程大纲

  • 图像基本知识:像素、色彩、图像格式
  • 图像处理技术:滤波、二值化、切割、形态学变换,尺度与旋转变换、图像梯度
  • 图像模式识别:直线与圆的检测、特征点检测、边缘检测
  • 图像模式识别:Blob检测、特征点检测、模板匹配
  • 神经网络基础:神经元结构、多层感知机、手写数字识别、损失函数
  • 神经网络基础:梯度下降、反向传播
  • 神经网络基础:Softmax回归、深度神经网络、卷积神经网络、服务器资源
  • 神经网络基础:循环神经网络、注意力机制 & Transformer、自然语言处理、强化学习、生成对抗网络
  • 大作业与答疑:象棋棋盘识别系统

Reference

  • Zhang, A., Lipton, Z., Li, M., & Smola, A. (2021). Dive into Deep Learning. arXiv preprint arXiv:2106.11342.