Binary Image Classification in TensorFlow

Binary or multi-class image classification using VGG16

A tool to detect powdery mildew in cherry leaves

A structural similarity index for binary or categorical images that works in 2D or 3D.

This repository is containing my Jupyter files.

This repository consists of classification of snakes species. It shows the whole progress and model used to achieve final accuracy. The model used are CNN(Convolutional Neural Network), MobileNetV2 and VGGNet. The final accuracy was achieved using transfer learning with model MobileNetV2

This repository contains Python code for generating a skin cancer detection model and utilizing it to detect skin cancer from user-inputted images or videos. The model architecture follows a sequential structure consisting of convolutional and pooling layers, with the final output layer using a sigmoid activation function.

Classify images in real time. Retrain this CNN with your own dataset. For the binary classification problem. Developed for detecting thumbs up or thumbs down.

In this repository, I put into test my newly acquired Deep Learning skills in order to solve the Kaggle's famous Image Classification Problem, called "Dogs vs. Cats".

This repository contains an ipython notebook which implements a Convolutional Neural Network to do a binary image classification. I used this to classify Cats vs Dogs and you can get the dataset from here https://www.kaggle.com/c/dogs-vs-cats/data . (This model trains with thousands of input images so be patient.)

Employing advanced techniques, the project seamlessly integrates binary and multiclass classifiers for character classification. It offers a comprehensive analysis and adeptly addresses challenges in the realm of computer vision.This project was part of my uOttawa Master's in Computer Vision course (2023).

Creating Neural Net from scratch using python , Numpy.

This repository contains code for a binary image classification model to detect pneumothorax using the ResNet-50 V2 architecture. It includes essential steps such as dataset splitting, image augmentation, model training, and a Streamlit application for user image upload and prediction.

Mini Project-III: Different type of Cat-Dog Binary Image Classification & also Multi-class classification on dogs breeds

CNN Model that classifies healthy and unhealthy food

Statistical Methods for Machine Learning project - Muffins Vs Chihuahuas