greentreeys Goto Github PK

aria

Retinal vessel analysis software for MATLAB

awesome-computer-vision

A curated list of awesome computer vision resources

awesome-deep-learning-papers

The most cited deep learning papers

awesome-deep-vision

A curated list of deep learning resources for computer vision

c3dis_slides

Slides from CSIRO's C3DIS

courses

fast.ai Courses

data-science-ipython-notebooks

Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

dataanalysis

deepfish

This repository provides cytogenetics related datasets to investigate the semantic segmentation

dlcampjeju

Deep Learning Camp Jeju

fundus-vessel-segmentation-tmbe

One of the first steps in automatic fundus image analysis is the segmentation of the retinal vasculature, which provides valuable information related to several diseases. In this work, we present an extensive description and evaluation of our method for blood vessel segmentation in fundus images based on a discriminatively trained, fully connected conditional random field model. This task remains a challenge largely due to the desired structures being thin and elongated, a setting that performs particularly poorly using standard segmentation priors, such as a Potts model or total variation. We overcome this difficulty by using a conditional random field model with more expressive potentials, taking advantage of recent results enabling inference of fully connected models almost in real-time. Parameters of the method are learned automatically using a structured output support vector machine, a supervised technique widely used for structured prediction in a number of machine learning applications. The evaluation of our method is performed both quantitatively and qualitatively on DRIVE, STARE, CHASEDB1 and HRF, showing its ability to deal with different types of images and outperforming other techniques, trained using state of the art features.

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

imfractal

A library to compute (multi)fractal dimensions of images written in Python.

inception-retrain

Standalone version of Tensorflow Inception Retrain

iterative-deep-learning

machine-learning-tutorials

machine learning and deep learning tutorials, articles and other resources

medical-screening-system

The system should be able to detect diseases in retinal images

mil-vt

mil.pytorch

PyTorch implementation of Multiple-instance learning

personalshare

Personal Stuff Share With Others

qix

Node.Js、Golang、Machine Learning、PostgreSQL、Deep Learning

quartz-epic

Quantitative Analysis of Retinal Vessel Topology and Size for EPIC

retina-unet

Retina blood vessel segmentation with a convolutional neural network

retina_dataset

Retina dataset containing 1) normal 2) cataract 3) glaucoma 4) retina disease

sklearn_tutorial

Materials for my scikit-learn tutorial

stanford_dl_ex

Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial

stockdatacrawling

Stock Data Crawling

tensorbox

Object detection in TensorFlow

tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

u-net

u-net for medical image segmentation