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DLIP
  • Introduction
  • Prerequisite
  • Image Processing Basics
    • Notes
    • Tutorial
    • LAB
  • Deep Learning for Perception
    • Notes
      • Lane Detection with Deep Learning
      • Overview of Deep Learning
      • Perceptron
      • Activation Function
      • Optimization
      • Convolution
      • CNN Overview
      • Evaluation Metric
      • LossFunction Regularization
      • Bias vs Variance
      • BottleNeck Unit
      • Object Detection
      • DL Techniques
    • Tutorial - PyTorch
    • LAB
    • Tutorial- Keras
    • Resource
  • Must Read Papers
  • DLIP Project
    • DLIP 2021 Projects
    • DLIP 2022 Projects
    • DLIP Past Projects
  • Installation Guide
    • Installation Guide for Pytorch
    • Anaconda
    • CUDA cuDNN
    • OpenCV
    • Framework
    • IDE
    • Ubuntu
    • ROS
  • Programming
    • Python_Numpy
    • Markdown
    • Github
    • Keras
    • PyTorch
  • Resources
    • Useful Resources
    • Githubarrow-up-right
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  1. Deep Learning for Perception

Notes

  • Overview of Deep Learningarrow-up-right

    • Deep Learning Basics: Introductionarrow-up-right

    • Deep Learning State of the Artarrow-up-right

    • CNN, Object Detectionarrow-up-right

  • Perceptronarrow-up-right

  • Activation Functionarrow-up-right

  • Optimizationarrow-up-right

  • Convolutionarrow-up-right

  • CNN Overviewarrow-up-right

  • Evaluation Metricarrow-up-right

  • LossFunction Regularizationarrow-up-right

  • Bias vs Variancearrow-up-right

  • BottleNeck Unitarrow-up-right

  • DL Techniquesarrow-up-right

    • Technical Strategy by A.Ngarrow-up-right

  • Object Detectionarrow-up-right

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Last updated 11 months ago