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)

Classification models trained on ImageNet. Keras.

A tensorflow2 implementation of some basic CNNs(MobileNetV1/V2/V3, EfficientNet, ResNeXt, InceptionV4, InceptionResNetV1/V2, SENet, SqueezeNet, DenseNet, ShuffleNetV2, ResNet).

CBAM implementation on TensowFlow

A PyTorch implementation of Inception-v4 and Inception-ResNet-v2.

DeepFake Detection: Detect the video is fake or not using InceptionResNetV2.

CBAM implementation on TensorFlow Slim

Supervised Classification of bird species :bird: in high resolution images, especially for, Himalayan birds, having diverse species with fairly low amount of labelled data [ICVGIPW'18]

SENet implementation on TensorFlow Slim

Models Supported: Inception [v1, v2, v3, v4], SE-Inception, Inception_ResNet [v1, v2], SE-Inception_ResNet (1D and 2D version with DEMO for Classification and Regression)

Tensorflow Implementation of FaceNet: A Unified Embedding for Face Recognition and Clustering to find the celebrity whose face matches the closest to yours.

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

This project involves automating the attendance system of RT Knits using Face Recognition. Due to Covid-19, people are obliged to wear masks hence, the system is successful in recognizing people despite wearing masks.

A tensorflow2 implementation of Inception_V4, Inception_ResNet_V1 and Inception_ResNet_V2.

Lung segmentation for chest X-Ray images with ResUNet and UNet. In addition, feature extraction and tuberculosis cases diagnosis had developed.

Regression in Convolutional Neural Network applied to Plant Leaf Count

Keras Implementation of major CNN architectures

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.

PredictiX is a comprehensive multi-disease prediction system built using the MERN stack and integrated with machine learning models. It accurately predicts lung cancer, breast cancer, diabetes, and heart disease, providing a seamless user experience for health diagnostics.

Implementation of GoogLeNet series Algorithm

Early Detection of Diabetic Retinopathy System, an application, uses machine learning to assess diabetic retinopathy risk. Input your health data and get results within seconds: Ranging from ['Mild', 'Moderate', 'Severe', 'No_DR']

A Deep Learning solver for the Shallow Water Equations

No description provided.

Ensemble based transfer learning approach for accurately classifying common thoracic diseases from Chest X-Rays

MATLAB Fashion Classification with Deep Learning.

Transfer Learning using InceptionResNetV2 to the Augmented Neuroimage Data for the Autism Spectrum Disorder (ASD) Classification, using ABIDE I dataset.

Landmark Recognition(Google Challenge on Kaggle) Using Transfer Learning

Capturing the special characteristics of Claude Monet's paintings in order to turn ordinary pictures into similar style paintings

The code and submissions for the Kaggle Plant Seedling Classification Challenge

A deep learning–based species classifier built for VLG’s Pixel Play competition, using InceptionResNetV2 with staged training and fine-tuning. The project utilizes custom dataset construction via web scraping and focuses on robust multi-class image classification using TensorFlow and Keras.