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Image Completion with Deep Learning in TensorFlow
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
Page to list the related works on deep learning for image retrieval.
A list of recent papers regarding deep reinforcement learning
Deep Residual Learning for Image Recognition
DeepVis Toolbox
Implementations of some popular Saliency Maps in Keras
Caffe for Deep Compression
Concolic Testing for Deep Neural Networks
The deeplearning algorithms implemented by tensorflow
deep reinforcement learning for personal research
Deformable Convolutional Networks
Deformable ConvNets V2 in PyTorch
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (TIP, 2017)
Test code of the CVPR 2017 paper "A Deep Regression Architecture with Two-Stage Re-initialization for High Performance Facial Landmark Detection"
Face recognition using Tensorflow
A tool using OpenCV to annotate images for image classification, optical character reading, ...
Torch implementation of ResNet from http://arxiv.org/abs/1512.03385 and training scripts
Implementation of Graph Convolutional Networks in TensorFlow
Toy Python implementation of http://www-nlp.stanford.edu/projects/glove/
Build Graph Nets in Tensorflow
Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.
https://2017.icml.cc/Conferences/2017/Schedule
https://icml.cc/Conferences/2018/Schedule
该资源为作者在CSDN的撰写Python图像处理文章的支撑,主要是Python实现图像处理、图像识别、图像分类等算法代码实现,希望该资源对您有所帮助,一起加油。
code for the paper "Improved Techniques for Training GANs"
I collected some papers about interpretable CNN and reorganized them here.
From stock prices to climate data, time series data are found in a wide variety of domains, and being able to effectively work with such data is an increasingly important skill for data scientists. This course will introduce you to time series analysis in Python. After learning about what a time series is, you'll learn about several time series models ranging from autoregressive and moving average models to cointegration models. Along the way, you'll learn how to estimate, forecast, and simulate these models using statistical libraries in Python. You'll see numerous examples of how these models are used, with a particular emphasis on applications in finance.
Implementations of selected inverse reinforcement learning algorithms.
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.