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maxpooling

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This model helps us classify 10 different real-life objects by undergoing training under tensorflow's CIFAR dataset which contains 60,000 32x32 color images with 6000 images of each class. I have made use of a stack of Conv2D and MaxPooling2D layers followed by a few densely connected layers.

  • Updated Jan 5, 2022
  • Jupyter Notebook

I used the MNIST dataset for the implementation of a handwritten digit recognition app. To implement this, will be using a special type of deep neural network called Convolutional Neural Networks. In the end, I also build a Graphical user interface(GUI) where you can directly draw the digit and recognize it straight away.

  • Updated Jun 30, 2023
  • Jupyter Notebook
Face-Mask-Detection-Real-Time-Computer-Vision

This repository contains code that implemented Mask Detection using MobileNet as the base model and Neural Network as the head model. Code draws a rectangular box over the person's face in red if no mask, green if the mask is on, with 99% accuracy in real-time using a live webcam. Refer to README for demo

  • Updated Jul 6, 2023
  • Jupyter Notebook

JavaFx Application for Convolutional Network to perfom Image Classification using Softmax Output Layer, Back Propagation, Gradient Descent, Partial Derivatives, Matrix Flattening, Matrix Unfolding, Concurrent Task, Performance Histogram, Confusion Matrix

  • Updated Jun 8, 2023
  • Java

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