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  1. πŸ‘©β€πŸ’» Works and Notes on CNNs

Introduction

πŸ”¦ Convolutional Neural Networks Codes

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Last updated 4 years ago

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This section will be filled by codes and notes gradually

πŸ‘©β€πŸ’» Codes

  1. 🌐 Tensorflow.js based hand written digit recognizer

βœ‹ RPS Dataset

  • Rock Paper Scissors is an available dataset containing 2,892 images of diverse hands in Rock/Paper/Scissors poses.

  • Rock Paper Scissors contains images from a variety of different hands, from different races, ages and genders, posed into Rock / Paper or Scissors and labelled as such.

πŸ”Ž All of this data is posed against a white background. Each image is 300Γ—300 pixels in 24-bit color

πŸ› CNN Debugging

We can get info about our CNN by

model.summary()

And the output will be like:

Layer (type)                 Output Shape              Param #   
=================================================================
conv2d_18 (Conv2D)           (None, 26, 26, 64)        640       
_________________________________________________________________
max_pooling2d_18 (MaxPooling (None, 13, 13, 64)        0         
_________________________________________________________________
conv2d_19 (Conv2D)           (None, 11, 11, 64)        36928     
_________________________________________________________________
max_pooling2d_19 (MaxPooling (None, 5, 5, 64)          0         
_________________________________________________________________
flatten_9 (Flatten)          (None, 1600)              0         
_________________________________________________________________
dense_14 (Dense)             (None, 128)               204928    
_________________________________________________________________
dense_15 (Dense)             (None, 10)                1290      
=================================================================

πŸ‘©β€πŸ’» For code in the notebook:

  • πŸ”Ž The original dimensions of the images were 28x28 px

  • 1️⃣ 1st layer: The filter can not be applied on the pixels on the edges

    • The output of first layer has 26x26 px

  • 2️⃣ 2nd layer: After applying 2x2 max pooling the dimensions will be divided by 2

    • The output of this layer has 13x13 px

  • 3️⃣ 3rd layer: The filter can not be applied on the pixels on the edges

    • The output of this layer has 11x11 px

  • 4️⃣ 4th layer: After applying 2x2 max pooling the dimensions will be divided by 2

    • The output of this layer has 5x5 px

  • 5️⃣ 5th layer: The output of the previous layer will be flattened

    • This layer has 5x5x64=1600 units

  • 6️⃣ 6th layer: We set it to contain 128 units

  • 7️⃣ 7th layer: Since we have 10 categories it consists of 10 units

😡 😡

πŸ‘€ Visualization

πŸ‘·β€β™€οΈ Network Visualization Tool

🧐 References

🐾

The visualization of the output of each layer is available πŸ”Ž

🌱
πŸ‘Ά Basic CNNs
πŸ‘€ CNN Visualization
πŸ‘¨β€πŸ‘©β€πŸ‘§β€πŸ‘§ Human vs Horse Classifier with CNN
🐱 Dog vs Cat Classifier with CNN
🎨 Multi-Class Classification
Classifier.js
MNISTData.js
index.html
Here
here
Netron ✨✨
Binary Cross-Entropy
RMSProp Explained
RMSProp in Tensorflow
Binary Classification
TensorFlow: an ML platform for solving impactful and challenging problems
Rock Paper Scissors Dataset