Search Results for "deep" - Page 11
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Showing 303 open source projects for "deep"
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Image classification models for Keras
Keras code and weights files for popular deep learning models
All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json. For instance, if you have set image_dim_ordering=tf, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, "Width-Height-Depth". Pre-trained weights can be automatically loaded upon instantiation (weights='imagenet'... -
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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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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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Caffe Framework
Caffe, a fast open framework for deep learning
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. -
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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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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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The Edge Machine Learning library
Machine learning algorithms for edge devices
Machine learning models for edge devices need to have a small footprint in terms of storage, prediction latency, and energy. One instance of where such models are desirable is resource-scarce devices and sensors in the Internet of Things (IoT) setting. Making real-time predictions locally on IoT devices without connecting to the cloud requires models that fit in a few kilobytes.These algorithms can train models for classical supervised learning problems with memory requirements that are... -
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Accord.NET Framework
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono. -
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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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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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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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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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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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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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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. -
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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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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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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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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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GLIntercept
GLIntercept is a OpenGL function call interceptor for Windows
...It captures real-time graphics API activity, shader sources, textures, and framebuffers, making it invaluable for performance tuning, reverse engineering, and debugging complex rendering problems. GLIntercept can inject itself into any OpenGL application and provide deep inspection capabilities, helping developers visualize pipeline behavior and diagnose rendering issues with minimal intrusion. -
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deemon
Deemon Scripting Language
...With a fully packed standard library including support for file-io, threads, atomics, pipes, math, file-system, sockets, randomization, hashing, serialization, a wide selection of emulated c/c++ headers and more, deemon provides a suitable environment for any application. Syntax is easy to read and understand and is mostly based on the common languages such as c/c++, java and python, though for those fascinated by it, reaches very deep and allows for pleasingly beautiful code to be written. If you wish to learn deemon, download any package and take a look at 'lib/tut' Note: If you've already used v100, you'll be happy to see how much deemon has grown in the five months that have passed. Keep up to date with deemon at: https://github.com/GrieferAtWork/deemon -
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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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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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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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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. ...
