This repository contains a Python-based image recognition project using TensorFlow and Keras. It leverages a pre-trained Convolutional Neural Network (CNN) model on the CIFAR-10 dataset to classify objects in images. The project supports image recognition from both local files and URLs.

Alertness detection inside vehicles or other places with straight eye alignment

The aim is to categorise and accurately identify the types and subtypes of breast cancer

An innovative traffic sign detection technique for precise and efficient identification

Grayscale image colorization using a U-Net CNN (with VGG-19) and perceptual loss.

Defect detection on metal shaft surfaces using Convolutional Neural Network

Real time face-mask detection using Deep Learning and OpenCV

Neural network that identifies and labels vegetables

For the practical implementation of this project , i have created an app on Streamlit and uploaded on Streamlit Cloud Cloud

Superhero Classifier Web App using Streamlit built on a custom CNN Image classifier

College project | Number recognition Kaggle challenge with dataset MNIST 🆒 😄 🐍 ✔️

conv networks to identify objects within images (classification + identification)

This API is designed to predict tomato diseases based on input images. The aim is to aid in the early detection of diseases in tomato plants to improve crop yield and reduce losses.

hyper-sinh: An Accurate and Reliable Activation Function from Shallow to Deep Learning in TensorFlow, Keras, and PyTorch

My College Final Project

Super-resolution using GANs. CNN, Image Classification and Image Upscaling.

This code trains a CNN in Keras to classify cell images (infected/uninfected). It sets up data generators, defines model architecture with convolutional layers, applies regularization, configures callbacks, and trains the model for binary classification.

AI integrated drone with agriculture disease detection capabilities.