The app is build using CNN and is deplyed on heroku server as a flask-python app.

An implementation of the iris flower classification using Keras on the iris dataset

This project is a web-based application that uses a Convolutional Neural Network (CNN) to detect brain tumors from MRI images. It allows users to upload MRI scans, which are then analyzed using a trained deep learning model to predict whether a brain tumor is present or not. The prediction results, along with user details, are stored in MongoDB.

COSC 6373 - Computer Vision - UH Spring 2025

My Smart Mirror Mark II project

Creating a CNN architecture and training the model to identify landmarks all over the world.

Codes for Deep Learning in Medicine course taken in 2019 spring.

Udacity Machine Learning Engineer Nanodegree Convolutional Neural Networks (CNN) Project: Dog Breed Classifier

A CNN to identify dog breeds (P2 - DLND)

Deepfake detection simple by image

DERM-AI: A deep learning–powered skin disease detection system built using Inception-ResNet-v2 and deployed via a Flask API. Upload an image and receive fast, accurate predictions for multiple skin conditions.

CNN for dog breed classification

Built with convolutional neural networks using Keras and Tensorflow

As we all know music is ubiquitous. We listen to music everywhere. Often we listen to music according to our playlists and most of the time the songs in playlist are grouped by the genre. So, classifying music according to genre is an important task. In this project I have used the GTZAN dataset which consists of 1000 songs divided into 10 genre…

This is a full stack web app, which Includes Frontend (HTMLCSS,JS), Backend(Flask), Machine Learning Model, Artificial Intelligence(Gemini), Firebase(Google)

🧵 Classify fashion images using a compact CNN model in TensorFlow/Keras, designed for the Fashion-MNIST dataset with easy execution in Google Colab.

🔍 Monitor network activity in real-time with LazyNet, a terminal-based tool that provides clear insights and management for processes and connections.