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3d-brain-segmentation

This is a repository containing code to Paper "Optimized High Resolution 3D Dense-U-Net Network for Brain and Spine Segmentation" published at MDPI Applied sciences journal - https://www.mdpi.com/2076-3417/9/3/404 .

3d-machine-learning

A resource repository for 3D machine learning

3d-mri-brain-tumor-segmentation-using-autoencoder-regularization

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

3dunet-tensorflow-brats18

3D Unet biomedical segmentation model powered by tensorpack with fast io speed

3dunet_abdomen_cascade

3dunetcnn

Keras 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation

adanet

Fast and flexible AutoML with learning guarantees.

albumentations

fast image augmentation library and easy to use wrapper around other libraries

attention-gated-networks

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

augmentor

Image augmentation library in Python for machine learning.

autoclint

A specially designed light version of Fast AutoAugment

autoimpute

Python package for Imputation Methods

awesome-dash

A curated list of awesome Dash (plotly) resources

awesome-docker

:whale: A curated list of Docker resources and projects

awesome-gan-for-medical-imaging

Awesome GAN for Medical Imaging

awesome-jupyter

A curated list of awesome Jupyter projects, libraries and resources

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

awesome-tflite

A curated list of awesome TensorFlow Lite models, samples, tutorials, tools and learning resources.

bmsg-gan

[MSG-GAN] Any body can GAN! Highly stable and robust architecture. Requires little to no hyperparameter tuning.

brain-tissue-segment-keras

Network: FCN, U-Net, Unet+Resblock(DeepUNet), Squeeze+UNet, DenseNet+UNet(DenseUnet)...

braindecode

Deep learning software to decode EEG or MEG signals

build-your-own-x

Master programming by recreating your favorite technologies from scratch.

ce-net

The manuscript has been accepted in TMI.

clothes_segmentation

mask R-CNN multi class classification example

cnn-dicom-segmentation

DICOM Image Segmentation with CNNs in Tensorflow

cnnbasedmedicalsegmentation

Code for reproducing the results of our paper on CNN-based medical image segmentation

convnet-drawer

Python script for illustrating Convolutional Neural Networks (CNN) using Keras-like model definitions

course-gitbook

Full Stack Deep Learning Online Course

cs156-machine-learning

Learning to apply core machine learning techniques — such as classification, perceptron, neural networks, support vector machines, hidden Markov models, and nonparametric models of clustering — as well as fundamental concepts such as feature selection, cross-validation and over-fitting. Programming machine learning algorithms to make sense of a wide range of data, such as genetic data, data used to perform customer segmentation or data used to predict the outcome of elections.

cs166-modeling-simulation-and-decision-making

Learning how to apply advanced decision techniques such as real options, Monte Carlo simulation, network concepts from graph theory, probability theory and statistical physics to analyze and predict the behavior of social, economic and transportation networks. Examples include project portfolio management, pharmaceutical drug development, oil and gas investment decisions as well as philanthropic portfolio decisions requiring high-stake tradeoffs in highly uncertain environments.