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In this project, we deploy the Bayesian Convolution Neural Networks (BCNN), proposed by Gal and Ghahramani [2015] to classify microscopic images of blood samples (lymphocyte cells). The data contains 260 microscopic images of cancerous and non-cancerous lymphocyte cells. We experiment with different network structures to obtain the model that return lowest error rate in classifying the images. We estimate the uncertainty for the predictions made by the models which in turn can assist a doctor in better decision making. The Stochastic Regularization Technique (SRT), popularly known as Dropout is utilized in the BCNN structure to obtain the Bayesian interpretation.
The Peter Moss Acute Myeloid/Lymphoblastic Leukemia classifiers are a collection of projects that use computer vision to classify Acute Myeloid/Lymphoblastic Leukemia in unseen images. The projects include classifiers made with Tensorflow, Caffe, Intel Movidius (NCS & NCS2), OpenVino and pure Python classifiers.
吴恩达《深度学习》系列课程笔记及代码
This is a modification of the previous work by using deep neural networks and it aims to detect 10 different cell types in Iron deficiency anemia, Thallasemia minor and Sickle cell anemia.
This is an implementation of ICML 2018 "Attention-based Deep MIL"
Implementation of Attention-based Deep Multiple Instance Learning in PyTorch
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
TensorFlow - A curated list of dedicated resources http://tensorflow.org
This repository is an attempt to list all malaria parasite imaging datasets (blood smears). Contributions welcome!
BCCD Dataset is a small-scale dataset for blood cells detection.
为我的博客写材料,并且学习,都是一些代码或者资料
Counting Red and White Blood Cells from Images
useful books on deep learning or machine learning
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Caffe implementation of multiple popular object detection frameworks
An open-source application for biological image analysis
👩🏿💻👨🏾💻👩🏼💻👨🏽💻👩🏻💻** AI 开发者项目列表 -- 分享大家都在做什么
Data Efficient & Weakly Supervised Computational Pathology on Whole Slide Images
Fine-tune CNN in Keras
Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:
repository for Community Mentor content related to the Johns Hopkins University Data Science Specialization on Coursera
Deep Learning Papers on Medical Image Analysis
Keras code and weights files for popular deep learning models.
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Zhu, Wentao, Qi Lou, Yeeleng Scott Vang, and Xiaohui Xie. "Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification." MICCAI 2017.
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.