awsaf49

EfficientNetV2

Implementation of EfficientNetV2 model in TensorFlow 2 Keras.

reinforcement-learning-an-introduction

Python Implementation of Reinforcement Learning: An Introduction

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

res-loglikelihood-regression

Code for "Human Pose Regression with Residual Log-likelihood Estimation", ICCV 2021 Oral

tf_ResNeSt_RegNet_model

tensorflow 2.x version of ResNeSt,RegNet,DETR

S-RAFNI

omnimatte

Brain-Tumor-Segmentation

Attention-Guided Version of 2D UNet for Automatic Brain Tumor Segmentation

imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

AReLU

AReLU: Attention-based-Rectified-Linear-Unit

tf_keras_gradcamplusplus

tensorflow.keras implementation of gradcam and gradcam++

GFPGAN

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

nnAudio

Audio processing by using pytorch 1D convolution network

class-balanced-loss

Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019

VideoSuperResolution

A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.

annotated_deep_learning_paper_implementations

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

triplet-attention

Official PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]

K3D-jupyter

K3D lets you create 3D plots backed by WebGL with high-level API (surfaces, isosurfaces, voxels, mesh, cloud points, vtk objects, volume renderer, colormaps, etc). The primary aim of K3D-jupyter is to be easy for use as stand alone package like matplotlib, but also to allow interoperation with existing libraries as VTK.

MedicalNet

Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and relative code.

YOLOX

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

Machine-Learning

Implementation of different ML Algorithms from scratch, written in Python 3.x

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

yolor

implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)

flexible-yolov5

More readable and flexible yolov5 with more backbone(gcn, resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer, etc) and (cbam，dcn and so on), and tensorrt

fds

Fast Data Science, AKA fds, is a CLI for Data Scientists to version control data and code at once, by conveniently wrapping git and dvc

MONAILabel

MONAI Label is an intelligent open source image labeling and learning tool.

tpu

Reference models and tools for Cloud TPUs.

keras-noisy-student

EfficientNet-L2 weights in Keras and retrieval script modified from qubvel/efficientnet

automl

Google Brain AutoML

decision-forests

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.