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
An Implementation of Fully Convolutional Networks in Tensorflow.
Classification models trained on ImageNet. Keras.
High level network definitions with pre-trained weights in TensorFlow
ImageNet pre-trained models with batch normalization for the Caffe framework
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)
Implement of Openpose use Tensorflow
An easy implement of VGG19 with tensorflow, which has a detailed explanation.
AI场景分类竞赛
Artificial Intelligence Learning Notes.
Pytorch Imagenet Models Example + Transfer Learning (and fine-tuning)
Learning and Building Convolutional Neural Networks using PyTorch
X-ray Images (Chest images) analysis and anomaly detection using Transfer learning with inception v2
Various CNN models for CIFAR10 with Chainer
Speaker identification with VGGVox network
TensorFlow implementation of real-time style transfer using feed-forward generation. This builds on the original style-transfer algorithm and allows for common personal computers to transform images.
⛵️ Implementation a variety of popular Image Classification Models using TensorFlow2. [ResNet, GoogLeNet, VGG, Inception-v3, Inception-v4, MobileNet, MobileNet-v2, ShuffleNet, ShuffleNet-v2, etc...]
Identifying numbers from bankcard, based on Deep Learning with Keras
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