2515 Open source projects that are alternatives of or similar to Dltk

This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"

DLTK Model Zoo

Datasets, tools, and benchmarks for representation learning of code.

DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy

Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)

This is Andrew NG Coursera Handwritten Notes.

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A curated list of awesome Distributed Deep Learning resources.

RadIO is a library for data science research of computed tomography imaging

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Fellow Oak DICOM for .NET, .NET Core, Universal Windows, Android, iOS, Mono and Unity

Support content for my blog

SincNet is a neural architecture for efficiently processing raw audio samples.

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A Tensorflow model for text recognition (CNN + seq2seq with visual attention) available as a Python package and compatible with Google Cloud ML Engine.

Service Classification based on Service Description

🎨 🎨 深度学习 卷积神经网络教程 ：图像识别，目标检测，语义分割，实例分割，人脸识别，神经风格转换，GAN等🎨🎨 https://dataxujing.github.io/CNN-paper2/

Python Library for Model Interpretation/Explanations

Descriptive Deep Learning

🔮Deep Learning for text made easy with AllenNLP

потоковый курс "Машинное обучение и анализ данных (Machine Learning and Data Mining)" на факультете ВМК МГУ имени М.В. Ломоносова

Slicer extensions index

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba

Code and other material for the book "Deep Learning and the Game of Go"

⚡High Performance DICOM Medical Image Parser in Go.

TensorFlow and Deep Learning Tutorials

Medical image preprocessing and augmentation toolkit for deep learning

Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlow, Caffe, PyTorch etc. as a Service on Kubernetes

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

Multi-platform, free open source software for visualization and image computing.

🚀 The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems!

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

Segment Source Distribution

Try out deep learning models online on Google Colab

A collection of notebooks of my Machine Learning class written in python 3

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

This toolbox is support material for the book on CNN (http://www.convolution.network).

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

Data-centric declarative deep learning framework

The Official Deep Learning Framework for Route-based Place Recognition

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MemeGen is a web application where the user gives an image as input and our tool generates a meme at one click for the user.

End-to-end one-class instance segmentation based on U-Net architecture for Data Science Bowl 2018 in Kaggle

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Bidirectional Attention Flow for Machine Comprehension implemented in Keras 2

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All DeepLearning4j projects go here.

A minimalist deep learning library in Javascript using WebGL + asm.js. Run convolutional neural network in your browser.