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Name: StoneHammer
Type: User
Name: StoneHammer
Type: User
Lecture Note&Code
[ICCV2019] RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment
🏞 A content-based image retrieval (CBIR) system
(Biological) Cell Tracker for Microscopy Image Analysis
昂达H410D4 IPC + i5 10400 核显
Code for paper "Hetero-center loss for cross-modality person re-identification"
The official repository of the 2019 Kidney and Kidney Tumor Segmentation Challenge
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
lung
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners
Presentation of MAG-SD
Multi Agent Reinforcement Learning using MalmÖ
A PyTorch implementation of the architecture of Mask RCNN
Mask R-CNN on Keras and TensorFlow,个人注释版
NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection.
BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagged large and had a space of 1GB+ . My work includes self laid neural network which was repeatedly tuned for one of the best hyperparameters and used variety of utility function of keras like callbacks for learning rate and checkpointing. Could have augmented the image data for even better modelling but was short of RAM on kaggle kernel. Other metrics like precision , recall and f1 score using confusion matrix were taken off special care. The other part included a brief introduction of transfer learning via InceptionV3 and was tuned entirely rather than partially after loading the inceptionv3 weights for the maximum achieved accuracy on kaggle till date. This achieved even a higher precision than before.
Pytorch implementation of Center Loss
生成模型的读书笔记,主要使用markdown,请使用jupyter做demo
Bag of Tricks and A Strong Baseline for Deep Person Re-identification
rw-diff code
SeGAN: Segmenting and Generating the Invisible (https://arxiv.org/pdf/1703.10239.pdf)
code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"
Social Relation Recognition TensorFlow
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.