American sign langauge detection using cnn
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Updated
Jul 10, 2023 - Jupyter Notebook
American sign langauge detection using cnn
Data augmentation is a technique of artificially increasing the training set by creating modified copies of a dataset using existing data. Here is a notebook of different augmentation techniques.
🌾🍀 An early crop disease discovery Deep Convolutional Neural Networks model using leaf symptom images.
For correctly predicting the crops from the images provided
Solid Waste Detection with Convolutional Neural Networks (CNN)
The augmented image processing for a cgi generated dataset of humans and horses using to train a CNN model.
Emotion Detection using Convolutional Neural Networks
Just a practice to implement CNN on one of my favouraite games
Train Your CNN model on any object without any need of your custom dataset by using webscraping
Classification using advanced Convolution Neural Networks and the Intel Image dataset, featuring 6 classes of color pictures in 150x150 pixels resolution.
It Contains a Model which Recognizes Handwritten letters using CNN (Convolutional Neural Network).
This project is a digit recognition app using a deep learning model trained on the MNIST dataset.
Using convolutional neural networks in Keras with Tensorflow backend to classify brain tumor MRI images among five classes.
predicting image category using convolutional neural networks
Jupyter notebooks creating Keras models to classify dog & cat breeds based on limited dataset, with and without transfer learning
Computer Vision using CNN on dataset consisting of real world images of humans & horses.
Ultrasound Image Recognition
A Repository of convolutional neural networks (CNN) trained on multiple different datasets
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