A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

Проект для обучения модели по классификации автомобилей по марке и модели

End-to-end Multiclass Dog Breed image classifier using TensorFlow 2.0

REST API to take in an image and return objects present with % predictions

Summary of ImageNet Papers

Diagnosing pneumonia with transfer learning

Transfer learning using a CNN pretrained on ImageNet.

Transfer learning: presentation and practical tutorial

GhostNetV2: Enhance Cheap Operation with Long-Range Attention

Exploration and implementation of an inverse image search using transfer learning and nearest neighbors search.

A bunch of notebooks experimenting with Caffe, TF, Keras, PyTorch, etc.

A deep learning image segmentation library and API on top of PyTorch.

In this project I built a model able to classify dog and cat images according to their breeds. I used the dataset from the Oxford Pets Kaggle competition, which consists of 7,349 training images and comprises 37 breeds of cats or dogs. I used Deep Learning, Computer Vision and Transfer Learning techniques.

Efficient Perturbation-Aware Distinguishing Score for Zero-Shot Neural Architecture Search

Segmentation models with pretrained backbones. PyTorch. for Google Colab cell motility segmentation example.

API to run model ResNet50

Pushing up the french accent and top-1 acc on "Imagenette" (A subset of Imagenet)

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.