Popular GitHub Repositories for Conll U

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

This is the repo for our new project Highly Accurate Dichotomous Image Segmentation

3D U-Net model for volumetric semantic segmentation written in pytorch

《深度学习与计算机视觉》配套代码

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

Use Google's BERT for named entity recognition （CoNLL-2003 as the dataset）.

Simple and Efficient Tensorflow implementations of NER models with tf.estimator and tf.data

[CVPR 2022] Official implementation of the paper "Uformer: A General U-Shaped Transformer for Image Restoration".

Real-Time Semantic Segmentation in Mobile device

The Tensorflow, Keras implementation of U-net, V-net, U-net++, UNET 3+, Attention U-net, R2U-net, ResUnet-a, U^2-Net, TransUNET, and Swin-UNET with optional ImageNet-trained backbones.

Auto-Update your M3U Playlists every day without needing an app, with the same link.

This repo contains code and a pre-trained model for clothes segmentation.

??? YOLO series of PaddlePaddle implementation, PP-YOLOE+, RT-DETR, YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv10, YOLO11, YOLOX, YOLOv5u, YOLOv7u, YOLOv6Lite, RTMDet and so on. ???

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

基于u-net，cv2以及cnn的中文车牌定位，矫正和端到端识别软件，其中unet和cv2用于车牌定位和矫正，cnn进行车牌识别，unet和cnn都是基于tensorflow的keras实现

U-Net Brain Tumor Segmentation

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

This is the template code to use BERT for sequence lableing and text classification, in order to facilitate BERT for more tasks. Currently, the template code has included conll-2003 named entity identification, Snips Slot Filling and Intent Prediction.