Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
翻译 - 使用生成对抗网络的逼真的单图像超分辨率
Classification models trained on ImageNet. Keras.
An Implementation of Fully Convolutional Networks in Tensorflow.
Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
#计算机科学#High level network definitions with pre-trained weights in TensorFlow
#计算机科学#Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
This is a code repository for pytorch c++ (or libtorch) tutorial.
#计算机科学#Computer vision based ML training data generation tool 🚀
翻译 - 基于计算机视觉的机器学习训练数据生成工具：火箭：
#计算机科学#food image to recipe with deep convolutional neural networks.
仅使用numpy从头开始实现神经网络,包括反向传播公式推导过程; numpy构建全连接层、卷积层、池化层、Flatten层；以及图像分类案例及精调网络案例等,持续更新中... ...
天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet
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
#计算机科学#Artificial Intelligence Learning Notes.
#计算机科学#Implement of Openpose use Tensorflow
#计算机科学#Pretrained deep learning models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet, etc.
RM Operation can equivalently convert ResNet to VGG, which is better for pruning; and can help RepVGG perform better when the depth is large.