Search Results for "deep" - Page 2
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Showing 41 open source projects for "deep"
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...The repository provides implementations of CNN-based methods to extract feature representations from images and use them for similarity-based retrieval. It focuses on applying deep learning techniques to improve upon traditional handcrafted descriptors by learning features directly from data. The code includes training and evaluation scripts that can be adapted for custom datasets, making it useful for experimenting with retrieval systems in computer vision. By leveraging CNN architectures, the project showcases how learned embeddings can capture semantic similarity across varied images. ...
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Euler
A distributed graph deep learning framework.
As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable for processing by existing deep learning models. Graph is a data type in non-Euclidean space and cannot be directly applied to existing methods, requiring a specially designed graph neural network system. Graph-based learning methods such as graph neural networks combine end-to-end learning with inductive reasoning, and are expected to solve a series of problems such as relational reasoning and interpretability that deep learning cannot handle. -
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Bloaty
Bloaty: a size profiler for binaries
Bloaty is a deep, accurate size profiler for native binaries that tells you where every byte comes from so you can shrink executables and libraries intelligently. It parses binary formats like ELF, Mach-O, and DWARF symbol/debug data without relying solely on toolchain heuristics, letting you attribute size to files, sections, symbols, templates, and even compilation units. -
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EVEAI is a Deep Learning Library based on python Keras and Tensorflow. EVEAI dll allows embedding inference images from keras models into user-written applications. Under Windows, the EVEAI training Tool provides services to train user specific image datasets and EVEAI dll provides services to existing Windows applications which support inference images.
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DaNNet
Deep Artificial Neural Network framework using Armadillo
DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network. -
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understand-plugin-framework
Demos to help understand plugin framwork
...The project is particularly useful for those interested in modular application design and dynamic feature loading. It highlights both the capabilities and challenges of plugin frameworks. Overall, it serves as a deep dive into Android extensibility mechanisms. -
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Tiramisu
Polyhedral compiler for expressing fast and portable data algorithms
...It provides a simple C++ API for expressing algorithms (Tiramisu expressions) and how these algorithms should be optimized by the compiler. Tiramisu can be used in areas such as linear and tensor algebra, deep learning, image processing, stencil computations and machine learning. The Tiramisu compiler is based on the polyhedral model thus it can express a large set of loop optimizations and data layout transformations. Currently, it targets (1) multicore X86 CPUs, (2) Nvidia GPUs, (3) Xilinx FPGAs (Vivado HLS) and (4) distributed machines (using MPI). ... -
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Sudoku Game Solver Generator
Standalone Complete Sudoku puzzle Game Solver Generator for Windows
...Also there is High Score table and built-in timer for professional players. The Sudoku generation algorithm used by this app is my ultimate proud. Primarily it was based on a Deep Neural Network. But I analyzed more than 100 scientific publications on Sudoku generation problem and have reduced the Deep Neural Network to a relatively simple and very elegant deterministic algorithm that works pretty fast. As a result, the app can generate Sudoku fields in 7 difficulty levels from 'Yellow Belt' to 'Sudoku Game Jedi Master'. ... -
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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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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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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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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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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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ODO is: 1) Real-Time ORM; 2) Real-Time DBMS like TimesTen; 3) Real-Time Grid like Coherence; with deep integration ORM+DBMS+Grid; Last News: ODO Becomes Commercial and public project was frozen.
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pRPL is a general-purpose parallel Raster Processing C++ programming Library. It enables the implementation of parallel raster-based algorithms without requiring a deep understanding of parallel computing, and greatly reduces the development complexity.
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The integration of the VM on most OS is not very deep: It sits on top of the OS, running as a simple app, and does not access most features of the OS. This project's aim is to deeply integrate with the OS to facilitate many services.
