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).

AI场景分类竞赛

CBAM implementation on TensowFlow

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

CBAM implementation on TensorFlow Slim

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

Supervised Classification of bird species 🐦 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.

Regression in Convolutional Neural Network applied to Plant Leaf Count

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.

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.

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.

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

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']