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

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

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

Build and end-to-end facial keypoint recognition system using computer vision techniques and deep learning.

Project created for Udacity course "Deep Learning"

Flask and TF Cat vs Dog Image Classifier

UI for Real-Time Smoking Detection.

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)

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

Implementation of and experimentation with image captioning models based on the Show, Attend and Tell paper. 🏞️

This project is used to identify the fake vehicle by using number plate and face recognition . Problem statement provided by KAVACH HACKATHON 2023 PSID = KVH-005

web application that help people grow healthy plants

An AI-powered web application that lets you upload CT images to instantly detect and visualize kidney stones using a custom deep-learning model, complete with confidence bars, high-res downloads, and a sleek, interactive Tailwind-CSS interface.