Name: Yingyi Wu (Jennifer)
Type: User
Company: UCLA Institute for Technology Advancement
Bio: Research in Biological Image Diagnosis, Deep Learning Models & Algorithms, e.g. Biomedical image localization and classification based on Neural Network.
Location: Suzhou, China
Blog: [email protected]
Yingyi Wu (Jennifer)'s Projects
An application I'm building to learn sails.js
AMI Medical Imaging (AMI) JS ToolKit for THREEJS
AngularJS - HTML enhanced for web apps!
医护微定制应用产品开发中的高级搜索面板
WAMP in JavaScript for Browsers and NodeJS
BinarySearchTrees, using C Language
Simpliest Bitcoind client for Dart
Bitcoin-related functions implemented in pure JavaScript
Bitcoin client library in JavaScript using Node.js / MongoDB
The most popular HTML, CSS, and JavaScript framework for developing responsive, mobile first projects on the web.
Tiny bootstrap-compatible WYSIWYG rich text editor
C3D is a modified version of BVLC caffe to support 3D ConvNets.
This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors
Caffe: a fast open framework for deep learning.
Caffe models in TensorFlow
Caffe fork that supports training with weighted samples http://caffe.berkeleyvision.org/
Custom Model for image segmentation
Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"
Chest CT Computer-Aided Detection For Pulmonary Nodules
Collective Knowledge extension for collaboratively evaluating and optimising performance of Caffe across diverse hardware, software and data sets (compilers, libraries, tools, models, inputs):
Caffe code and prototxt files for the CNN Design Patterns paper
Computer Vision and Pattern Recognition
Bitcoin library written in Google Dart (dartlang.org).
Recursive Object.assign()
some materials about deep learning on medical image like x-rays, MRI, CT
Deep Residual Learning for Image Recognition