Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
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Updated
Feb 22, 2024 - Python
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Classification models trained on ImageNet. Keras.
An Implementation of Fully Convolutional Networks in Tensorflow.
High level network definitions with pre-trained weights in TensorFlow
This implements training of popular model architectures, such as AlexNet, ResNet and VGG on the ImageNet dataset(Now we supported alexnet, vgg, resnet, squeezenet, densenet)
ImageNet pre-trained models with batch normalization for the Caffe framework
Artificial Intelligence Learning Notes.
Implement of Openpose use Tensorflow
Pretrained deep learning models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet, etc.
Learning and Building Convolutional Neural Networks using PyTorch
An easy implement of VGG19 with tensorflow, which has a detailed explanation.
Pytorch Imagenet Models Example + Transfer Learning (and fine-tuning)
PyTorch implementation of DeepDream algorithm
Various CNN models for CIFAR10 with Chainer
X-ray Images (Chest images) analysis and anomaly detection using Transfer learning with inception v2
⛵️ Implementation a variety of popular Image Classification Models using TensorFlow2. [ResNet, GoogLeNet, VGG, Inception-v3, Inception-v4, MobileNet, MobileNet-v2, ShuffleNet, ShuffleNet-v2, etc...]
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