Search Results for "deep" - Page 6
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Showing 150 open source projects for "deep"
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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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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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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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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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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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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. ... -
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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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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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Embedded Firmware Library
Library for typical microcontroller- and peripheral functions
Embedded developers always use their favorite controllers, and if you want to modify open source code, you often have to dive deep in the datasheet of that controller. The "Embedded Firmware Library" is a project which offers a kind of API to control the controller-functions and the functions of the peripheral units on a certain board. As an application developer, you don't have to know anything about the registers of the controller. And you can write controller- and board-independent code. ... -
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CURRENNT
CUDA-enabled machine learning library for recurrent neural networks
CURRENNT is a machine learning library for Recurrent Neural Networks (RNNs) which uses NVIDIA graphics cards to accelerate the computations. The library implements uni- and bidirectional Long Short-Term Memory (LSTM) architectures and supports deep networks as well as very large data sets that do not fit into main memory. -
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Aspects
Library for aspect oriented programming in Objective-C and Swift
...It allows you to add code to existing methods per class or per instance, whilst thinking of the insertion point e.g. before/instead/after. Aspects automatically deals with calling super and is easier to use than regular method swizzling. Aspects hooks deep into the class hierarchy and creates dynamic subclasses, much like KVO. There's known issues with this approach, and to this date (February 2019) I STRICTLY DO NOT RECOMMEND TO USE Aspects IN PRODUCTION CODE. We use it for partial test mocks in, PSPDFKit, an iOS PDF framework that ships with apps like Dropbox or Evernote, it's also very useful for quickly hacking something up. ... -
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A simple library for cloning java objects. And it can do it in three ways. The shallow copy, the serialized copy and the deep clone. It is useful if you need to detach an entity from an EntityManager.
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FastImageEx
Image format to processing images on Delphi
This package defines an image format that was designed to be easily processed. The image can contain multiple channels. 1, 3 and 4 are common values but any number of channels is possible. This version defines channels with 8, 16 or 32 bits deep and allows mixing different types of channels in the same image. Each channel is stored in a map separated from other channels and can be independently processed without requiring any additional manipulation. -
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This simple project provides a way to efficiently calculate the actual memory use of any Java object. The class makes use of the JVMs own instrumentation support to calculate the object memory use in a portable way.
