Showing 268 open source projects for "deep"

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  • 1
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. ...
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  • 2
    iRate

    iRate

    Library to promote iPhone and Mac App Store apps

    iRate is a small utility for iOS/macOS apps that encourages users to rate your app after they’ve had enough exposure to form an opinion. Instead of nagging on first launch, it tracks usage metrics like number of launches or days since install and only prompts when thresholds are met. The goal is to increase high-quality, voluntary ratings while avoiding the fatigue that comes from aggressive dialogs. You configure the behavior through a handful of properties, and the library handles the...
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  • 3
    cnn-benchmarks

    cnn-benchmarks

    Benchmarks for popular CNN models

    ...Overall, cnn-benchmarks is a practical tool for performance analysis in deep learning workflows.
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  • 4
    Caffe2

    Caffe2

    Caffe2 is a lightweight, modular, and scalable deep learning framework

    Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind. Caffe2 is a deep learning framework that provides an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. You can bring your creations to scale using the power of GPUs in the cloud or to the masses on mobile with Caffe2’s cross-platform libraries. ...
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  • 5
    Orkney

    Orkney

    Orkney Testframework

    ...Test steps are used like bricks to create test cases while test groups collect test cases and other test groups to create a test suite. Test cases are written in a simple text language thus allowing composition of cases from test steps without deep programming knowledge. Reports are created in text and in XML format, the latter are converted to a human readable form when using a standard web browser.
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  • 6
    TensorFlow World

    TensorFlow World

    Simple and ready-to-use tutorials for TensorFlow

    ...The explanations are present in the wiki associated with this repository. There are different motivations for this open source project. TensorFlow (as we write this document) is one of / the best deep learning frameworks available. The question that should be asked is why has this repository been created when there are so many other tutorials about TensorFlow available on the web? Deep Learning is in very high interest these days - there's a crucial need for rapid and optimized implementations of the algorithms and architectures. ...
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  • 7
    fast-neural-style

    fast-neural-style

    Feedforward style transfer

    ...It also provides insights into the underlying techniques used in neural style transfer, making it both a practical tool and a learning resource. By combining performance and quality, it enables creative applications in image processing and design. Overall, fast-neural-style showcases how deep learning can be used for real-time artistic transformations.
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  • 8
    Caffe

    Caffe

    A fast open framework for deep learning

    Caffe is an open source deep learning framework that’s focused on expression, speed and modularity. It’s got an expressive architecture that encourages application and innovation, and extensible code that’s great for active development. Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around.
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  • 9
    Swift AI

    Swift AI

    The Swift machine learning library

    Swift AI is a high-performance deep learning library written entirely in Swift. We currently offer support for all Apple platforms, with Linux support coming soon. Swift AI includes a collection of common tools used for artificial intelligence and scientific applications. A flexible, fully-connected neural network with support for deep learning. Optimized specifically for Apple hardware, using advanced parallel processing techniques.
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  • 10
    Grenade

    Grenade

    Deep Learning in Haskell

    Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only...
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  • 11
    Face Verification Experiment

    Face Verification Experiment

    Original Caffe Version for LightCNN-9. Highly recommend to use PyTorch

    face_verification_experiment is a research repository focused on experiments in face verification using deep learning. It provides implementations and scripts for testing different neural network architectures and training strategies on face recognition and verification tasks. The project is designed to help researchers and practitioners evaluate the performance of models on standard datasets and explore techniques for improving accuracy.
    Downloads: 1 This Week
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  • 12
    odtReportSQL

    odtReportSQL

    Defines a complete reports/documents system for WAMP applications

    ...Based on templates created using OpenOffice (.odt files): templates can be of any size (A4, A3...) and multipage. On templates:: - Simple substitution based on couples #field#/value - Blocks and nested blocks duplication (any deep) or deletion - Pictures substitution The HTML User Inteface is build by System and can be easy added at existing php applications. This system is DB driven, using 2 tables to define all templates To add a new document is only required to update DB. Sources in github https://github.com/msillano/odtReportSQL Install: download all files in www/my_app/ see install.txt file
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  • 13
    PrettyTensor

    PrettyTensor

    Pretty Tensor: Fluent Networks in TensorFlow

    Pretty Tensor is a high-level API built on top of TensorFlow that simplifies the process of creating and managing deep learning models. It wraps TensorFlow tensors in a chainable object syntax, allowing developers to build multi-layer neural networks with concise and readable code. Pretty Tensor preserves full compatibility with TensorFlow’s core functionality while providing syntactic sugar for defining complex architectures such as convolutional and recurrent networks.
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  • 14
    React Fiber Architecture

    React Fiber Architecture

    A description of React's new core algorithm, React Fiber

    The React Fiber Architecture project is a detailed technical document that explains the internal design and behavior of React Fiber, the core algorithm that powers modern React rendering. Rather than being a traditional code library, it serves as an educational deep dive into how React manages updates, scheduling, and reconciliation under the hood. The document explores how Fiber replaces the older stack-based reconciliation algorithm with a more flexible system that breaks rendering work into incremental units. This enables advanced features such as interruptible rendering, prioritization of updates, and smoother user interfaces during complex operations. ...
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  • 15
    json4sapnw

    json4sapnw

    Another JSON extension for SAP ABAP

    ...It comes in the customer exchange namespace /CEX/ and has to be installed as an SAP transport request. The addon supports object oriented JSON methods to process deep structured JSON data. Building JSON data from SAP data objects and parsing JSON data back to SAP data objects are supported. See the WIKI for some examples. Thanks to the SAP community and especially to Rüdiger Plantiko for the basic work (http://ruediger-plantiko.blogspot.de/2010/12/ein-json-parser-in-abap.html). Enjoy! ...
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  • 16
    CRFasRNN

    CRFasRNN

    Semantic image segmentation method described in the ICCV 2015 paper

    CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps.
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  • 17
    Rendr

    Rendr

    Render your Backbone.js apps on the client and the server

    Rendr is a small library that allows you to run your Backbone.js apps seamlessly on both the client and the server. Allow your web server to serve fully-formed HTML pages to any deep link of your app, while preserving the snappy feel of a traditional Backbone.js client-side MVC app. We believe there has to be a better way to build rich web apps today. In the last few years, we've seen more of the application moved to the client-side, with JavaScript representations of views, templates, and models. This enables us to build interactive, native-style single-page apps, but splitting your app into two distinct codebases (often using different languages for client and server) also creates challenges for performance, maintainability, and SEO. ...
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  • 18
    iOS Tech Frontier

    iOS Tech Frontier

    Tanslates high-quality iOS technology, open source libraries

    iOS Tech Frontier is a curated, deep-dive repository of advanced technical knowledge around the iOS operating system and ecosystem, designed primarily for intermediate to advanced developers who want to understand beyond SDK basics and build highly performant, robust applications. Instead of simple how-to recipes, the project collects detailed explanations, system internals analyses, and real-world insights into core subsystems like memory management (ARC), threading and Grand Central Dispatch, Objective-C/Swift runtime behavior, UIKit rendering pipelines, and effective use of concurrency. ...
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  • 19
    Awesome Recurrent Neural Networks

    Awesome Recurrent Neural Networks

    A curated list of resources dedicated to RNN

    A curated list of resources dedicated to recurrent neural networks (closely related to deep learning). Provides a wide range of works and resources such as a Recurrent Neural Network Tutorial, a Sequence-to-Sequence Model Tutorial, Tutorials by nlintz, Notebook examples by aymericdamien, Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow, Keras (Tensorflow / Theano)-based modular deep learning library similar to Torch, char-rnn-tensorflow by sherjilozair, char-rnn in tensorflow, and much more. ...
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  • 20

    MDA

    Molecular Dynamics Analyzer (MDA)

    MDA is a 3D single-particle tracking software that explicitly addresses fluorescence microscopy experiments deep in living specimens. It is capable of minimizing the systematic error that occurs with astigmatism-based 3D techniques owing to the aberrations induced by the refractive index mismatch. In contrast to existing techniques, the method determines the aberration directly from the acquired 2D image stream by exploiting the inherent particle movement and the redundancy introduced by the astigmatism. ...
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  • 21
    Human AI Net

    Human AI Net

    a Human and Artificial Intelligence Network

    ...The main data format is, from xorlisp which is also in progress, immutable binary forest nodes, so if millions of people build that together nobody can damage or change anyone else's data since its all constant. You dont change variables. You create new data that points at existing constant data, as deep as you need it. I have mindmap lists, definitions, and 2 editable properties working that way with 2 kinds of event listeners that work locally. Its not a networked system yet, but the datastructs are ready to scale with it.
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  • 22
    Mori

    Mori

    ClojureScript's persistent data structures and supporting API

    Mori brings ClojureScript's efficient persistent data structures and functional APIs into vanilla JavaScript, enabling immutability and functional programming patterns with performant collections in JS. The installed package contains a single optimized JavaScript file mori.js. Load mori in your Node.js programs as you would any other module. For vectors and maps we provide efficient thaw and freeze operations. All Mori maps and sets support all the non-mutating methods of the proposed ES6...
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  • 23

    Super CSV

    A fast, programmer-friendly, free CSV library for Java

    ...This SourceForge page will remain, but with limited functionality (please go to GitHub to report issues and for project downloads). It is highly configurable, and supports reading and writing with POJOs, Maps and Lists. It also has support for deep-mapping and index-based mapping with POJOs, using the powerful Dozer extension. Its flexible 'Cell Processor' API automates data type conversions (parsing and formatting Dates, Integers, Booleans etc) and enforces constraints (mandatory columns, matching against regular expressions etc) - and it's easy to write your own if required. ...
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  • 24

    Immutable Sparse Wave Trees (WaveTree)

    Realtime bigdata tool for bit strings up to 2^63 based on AVL forest

    Realtime bigdata tool at the bit level based on immutable AVL forest which can be run in memory or, in future versions, as a merkle forest like a blockchain. Main object is a sparse bit string (Bits) that efficiently scales up to 2^63 bits normally compressed as forest has duplicated substrings. Bits objects support reading bit, byte, short, int, or long (Java primitives) at any bit index in 64 bit range. Example: instead of building a class to hold a header and then data, represent all of...
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  • 25
    ConvNetJS

    ConvNetJS

    Deep learning in Javascript to train convolutional neural networks

    ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. ...
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