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Name: Happy
Type: User
Name: Happy
Type: User
A collection of research articles, blog posts, slides and code snippets about deep learning in applied settings.
The most cited deep learning papers
Awesome GAN for Medical Imaging
:metal: awesome-semantic-segmentation
Using BM3D to denoise,the code I'm modified is from https://github.com/MarkPrecursor/BM3D_Denosing.git
Class Activation Mapping
NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
Repo for the Deep Reinforcement Learning Nanodegree program
Deep Learning Book Chinese Translation
Python implementation of Stacked Denoising Autoencoders for unsupervised learning of high level feature representation
Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"
Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR2018)
Few Shot Semantic Segmentation Papers
FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising (TIP, 2018)
Code for finetuning AlexNet in TensorFlow >= 1.2rc0
Internship status of companies - COVID-19
Image augmentation for machine learning experiments.
Deep Learning for humans
Keras implementation of class activation mapping
A practical example of image classifier with Keras 2.x and TensorFlow backend, using the Kaggle Cats vs. Dogs dataset. By taking advantage of Keras' image data augmentation capabilities (and also random cropping), we were able to achieve 99% accuracy on the trained model with only 2,000 images in the training set.
Fine tuning inception v3 on Kaggle dogs-vs-cats dataset
Keras implementations of Generative Adversarial Networks.
oct.15 learn how to use keras
VGG, RasNet and Inception architectures transfer learning
Python code for generating Leung-Malik (LM) filter bank that is typically used in texture analysis and classification.
Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
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.