julieli

julieli's Stars

• amusi/CVPR2024-Papers-with-Code

  CVPR 2024 论文和开源项目合集

  18.7k2912032.6k

• microsoft/Swin-Transformer

  This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

  Language:Python14.2k1273182.1k

• colmap/colmap

  COLMAP - Structure-from-Motion and Multi-View Stereo

  Language:C++8k1742.1k1.6k

• InsaneLife/ChineseNLPCorpus

  中文自然语言处理数据集，平时做做实验的材料。欢迎补充提交合并。

  Language:Python4.3k879789

• Beckschen/TransUNet

  This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

  Language:Python2.5k12160515

• bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets

  Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet

  Language:Python2k1766351

• ozan-oktay/Attention-Gated-Networks

  Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

  Language:Python1.9k350424

• colmap/pycolmap

  Python bindings for COLMAP

  Language:C++93518159129

• microsoft/SoftTeacher

  Semi-Supervised Learning, Object Detection, ICCV2021

  Language:Python90624225122

• srianant/kalman_filter_multi_object_tracking

  Multiple object tracking using Kalman Filter and Hungarian Algorithm - OpenCV

  Language:Python5451117165

• ShuoYang-1998/Few_Shot_Distribution_Calibration

  [ICLR2021 Oral] Free Lunch for Few-Shot Learning: Distribution Calibration

  Language:Python4735071

• GoogleCloudPlatform/covid-19-open-data

  Datasets of daily time-series data related to COVID-19 for over 20,000 distinct locations around the world.

  Language:Python47024177131

• wetliu/energy_ood

  Language:Python40373565

• MayankSingal/PyTorch-Image-Dehazing

  PyTorch implementation of some single image dehazing networks.

  Language:Python36171161

• Mehrdad-Noori/Brain-Tumor-Segmentation

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

  Language:Python21751735

• MoleImg/Attention_UNet

  Raw implementation of attention gated U-Net by Keras

  Language:Python1493543

• foolwood/VisualTracking-Toolkit

  Powerful visualization tool (still under development)

  Language:TeX1488236

• anhenghuang/dehaze

  实现暗通道去雾算法 Realizing 'Single Image Haze Removal Using Dark Channel Prior'

  Language:Python1332147

• nupurkmr9/S2M2_fewshot

  Language:Python11253120

• Kai-46/ColmapForVisSat

  Adapted COLMAP intended to work with satellite images

  Language:C545311

• MohsenFayyaz89/SCT

  SCT: Set Constrained Temporal Transformer for Set Supervised Action Segmentation (CVPR2020) https://arxiv.org/abs/2003.14266

  Language:Python38734

• jowoojun/biovec

  ProtVec can be used in protein interaction predictions, structure prediction, and protein data visualization.

  Language:Python33219

• bperezorozco/ordinal_tsf

  Language:Jupyter Notebook295211

• TebogoNakampe/TMIP-2019-nCoV-Recognition

  Treatise of Medical Image Processing (TMIP) v0.2.0

  Language:Python6306

• Jafar-Abdollahi/Automated-detection-of-COVID-19-cases-using-deep-neural-networks-with-CTS-images

  The use of advanced artificial intelligence (AI) techniques combined with radiological imaging can be useful for accurate diagnosis of the disease and can also help overcome the shortage of specialist physicians in remote villages. In this project, a new model for automatic detection of covid-19 using raw chest X-ray images is presented. The proposed model is designed to provide an accurate diagnosis for binary classification (COVID vs. pneumonia ) and multi-classification (covid, pneumonia, nodel, boronshit, normal). Our model produces 99.08% classification accuracy for binary classifications and 95.02% for multi-class cases. The DarkNet model was used in our study as a classification where you only look at the real-time object recognition system once (YOLO(v3)). We applied 17 layers of the convolution and applied different filters on each layer. Our model can be used to help radiologists discredit their initial screening and can also be used over the cloud for rapid screening of patients.

  Language:Jupyter Notebook5111

• GRSEB9S/DeepMEMM

  This is an implementation of a Deep Maximum Entropy Markov Model in PyTorch, that uses the Viterbi algorithm for inference to solve the task of Named Entity Recognition.

  Language:Python4103

• asherbar/MEMM-Viterbi

  Language:Python1200

• julieli/Swin-Unet

  The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"

  Language:Python1100

• leslieAIbin/ms-tcn-pytorch

  MS-TCN with pytorch, contains complete executable files.

  Language:Python1100

• tusharsince96/Attendance-System-Using-Image-Recognition-In-Covid-19-Situation

  The idea aims in creating an Attendance project that will use webcam to detect faces and record the attendance live in an excel sheet. In a situation like today when we are facing a covid-19 pandemic, it becomes very important to maintain social distancing norms and reduce the risk of contraction of coronavirus. A facial recognition system will improve efficiency and enable institutions to become a digitalized workplace with complete social distancing norms and with zero contact. This project aims in recognizing image of a people even with mask on their face and the best part of the project is that it won’t permit authentication to the people if they are not wearing their mask.

  Language:Python1100