An image classification app built using Django 4, Django REST Framework 3, Next.js 12, and Material UI 5. The app uses Inception-ResNet-v2 to classify images selected by the user.

This repository hosts the Cervical Cancer Image Classification project, a comprehensive effort aimed at improving the classification accuracy of Squamous Cell Carcinoma (SCC) through advanced deep learning models and ensemble techniques. The project utilizes the Herlev dataset.

Swin Transformer + Inception-ResNet = Improved Performance ✨ Evaluated on a Retinal OCT dataset.

Address the crowd counting problem on the Mall dataset (sparse) by exploring regression-based (Xception) and density-based (CSRNet) approaches.

Diabetic Retinopathy Predictor System, a Flask-based web app, uses machine learning to assess diabetic retinopathy risk. Input your health data and get results within seconds: Ranging from ['Mild', 'Moderate', 'Severe', 'No_DR']

benchmark of object detection algorithms for license plate detection

Gathering and labeling data for an image-text fusion model for flavor classification of food based on recipes. Generating images using stable diffusion models, and using deep classification models like BERT, BiLSTM, and InceptionResnet.

Explore diverse computer vision projects using Transfer Learning(TL), Convolutional Neural Networks (CNN), Autoencoder and more in this collaborative repository

End-to-end Image Classification using Deep Learning toolkit for custom image datasets. Features include Pre-Processing, Training with Multiple CNN Architectures and Statistical Inference Tools. Special utilities for RAM optimization, Learning Rate Scheduling, and Detailed Code Comments are included.

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

Explore my comprehensive collection of AI models for blood cancer detection. Leveraging deep learning and medical imaging, these models aim to revolutionize early diagnosis and treatment, making a significant impact on the battle against blood cancers. #AI #HealthcareInnovation

A from-scratch SOTA PyTorch implementation of the Inception-ResNet-V2 model designed by Szegedy et. al., adapted for Face Emotion Recognition (FER), with custom dataset support.

Classify the severity stages of Diabetic Retinopathy

This project is a web application that uses YOLOv5 and InceptionResNetV2 models for license plate detection and Optical Character Recognition (OCR) text extraction. The web applications were built using streamlit and flask

This project was part of the MLx Cases section of the OxML 2023 summer school.

A Deep Learning solver for the Shallow Water Equations

Coloring black and white images using autoecoders and transfer learning

Diabetic Retinopathy Detection Using Inception Resnet

Implementation of GoogLeNet series Algorithm