Search Results for "network data speed"
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Showing 27 open source projects for "network data speed"
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Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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Failed Payment Recovery for Subscription BusinessesFlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
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TIGRE
TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox
TIGRE is an open-source toolbox for fast and accurate 3D tomographic reconstruction for any geometry. Its focus is on iterative algorithms for improved image quality that have all been optimized to run on GPUs (including multi-GPUs) for improved speed. It combines the higher-level abstraction of MATLAB or Python with the performance of CUDA at a lower level in order to make it both fast and easy to use. TIGRE is free to download and distribute: use it, modify it, add to it, and share it. Our... -
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NeuroJSON
Scalable, searchable and verifiable neuroimaging data exchange platfor
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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xfemm
Cross platform electromagnetics finite element analyisis based on FEMM
...Development of xfemm now takes place on Github here: https://github.com/REOptimize-Systems/xfemm xfemm is a refactoring of the core algorithms of the popular Windows-only FEMM (Finite Element Method Magnetics, www.femm.info) to use only the standard template library and therefore be cross-platform. The codes can be used as a library, standalone executables, or through the advanced Matlab/Octave interface, which uses direct data exchange at the memory level rather than the original FEMM ActiveX or file-based interface, for much improved communication speed. If you use xfemm, particularly for industrial work, but also academic, it will be greatly appreciated if you could write an email stating this and how it has supported your work. This is a low-cost way to ensure further development and maintenance will continue! -
The Original Buy Center Software.VAN sources private-party vehicles from over 20 platforms and provides all necessary tools to communicate with sellers and manage opportunities. Franchise and Independent dealers can boost their buy center strategies with our advanced tools and an experienced Acquisition Coaching™ team dedicated to your success.
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cnn-for-image-retrieval is a research-oriented project that demonstrates the use of convolutional neural networks (CNNs) for image retrieval tasks. 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...
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SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
...It includes training scripts, evaluation code, and pre-trained models that achieve strong results on popular benchmarks such as AFW, PASCAL Face, FDDB, and WIDER FACE. The framework is optimized for speed and accuracy, making it suitable for both academic research and practical applications in computer vision. -
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Faster R-CNN
Object detection framework based on deep convolutional networks
This repository provides a MATLAB / Caffe re-implementation of the Faster R-CNN object detection framework (originally from Ren et al. 2015). The Faster R-CNN architecture combines a Region Proposal Network (RPN) with a Fast R-CNN style detection network to share convolutional feature maps and thus speed up detection. The repo includes code to train, test, and deploy Faster R-CNN models under the MATLAB / Caffe environment, example configuration files, and model checkpoints. Multiple configuration files for different datasets and architectures. ... -
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The purpose of the Freely Moving Animal (FMA) Toolbox is to help analyze electrophysiological and behavioral data recorded from freely moving animals.
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GTK+ IOStream
GTK+iostream, Data plots, ORB, Neural Networks, WSOLA
Create GTK+ interfaces using IOStream style code. Its simple and quick! Also providing simple data plotting (similar to Matlab/Octave), ORB (Object Request Broker), and Neural Network computations. You can create GTK+ GUIs in a few lines of code. Labels<<"Thanks for reading"; (HBox<<Labels).show(); or even one line : (HBox() << (Labels()<<"Thanks for reading")).show(); Inline code destructs the classes, but leaves the widgets/callbacks operating. -
Most modern and flexible cloud platform for MLM companiesFor direct selling (MLM) companies, from startup to well established enterprises with millions of distributors across the world
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RAFTS3
Rapid Alignment Free Tool for Sequences Similarity Search
RAFTS3 can perform high-speed protein search comparisons locally using a desktop computer or laptop. RAFTS3 performed searches many times faster than those with BLASTp against large protein databases such as NR and Pfam, with a small loss of sensitivity depending on the similarity degree of the sequences. RAFTS3 is a new alternative for fast comparison of protein sequences, genome annotation and biological data mining. -
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K-Level 2.0 [revised]
An application of leveling network adjustment using Matlab
This is an application of leveling network adjustment based on Matlab. The method used in this application is least square adjustment. User can enter the leveling data directly or by reading a text file. -
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OARS Android IMU & GPS Data Logger
OARS - Orientational Awareness Reaction Systems
...Along with a built in processor, it can calculate movements along 9-axis. Depending on platform and app setting, OARS can record sensor values at a rate up to 100hz, or 100 positions per second. GPS data such as Longitude, Latitude, Direction, Speed, and Elevation, are also logged at approximately 1hz, or 1 update per second. Giving you the ability to precisely map an equipped objects location, orientation, and rate of movement along any plane with extreme accuracy. -
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nail_systems_biology
NAIL is a toolset for network analysis in the life sciences
...Modelling biological systems as networks (graphs) is becoming a common approach in the life sciences. However, different algorithms typically use different input and output data types, are implemented using different technologies, and are demonstrated by application to different biological problems. Because of this, the primary goal of the NAIL project is to provide a straightforward way to use network approaches in the life sciences, and to apply a variety of techniques quickly and easily on the same data. -
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METAlab GTG
Matlab toolbox to run a GLM on graph theoretic properties in MRI data
This Matlab toolbox runs a GLM on graph theoretic network properties in brain networks. The GLM accepts continuous & categorical between-participant predictors and categorical within-participant predictors. Significance is determined via non-parametric permutation tests. The toolbox allows testing of both fully connected and thresholded networks (based on a range of thresholds). The toolbox also provides a data processing path for resting state fMRI data. -
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RIPE (Regulatory network Inference from joint Perturbation and Expression data) is a novel three-step method that integrates both perturbation data and steady state gene expression data in order to estimate a regulatory network. The ripe package is written in R, with additional functionality provided by a MATLAB executable file. The executable file uses a runtime engine called the MATLAB Compiler Runtime (MCR).
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Systems Glycobiology
Glycosylation Network Analysis Toolbox (GNAT)
...The second version of this software (GNATv2beta.zip) upgrades the original GNAT program with additional features that are geared towards incorporating glycan-structure experimental data into the simulation environment. For information about GNAT installation and usage, please see the GettingStarted.pdf file enclosed in the package. To cite GNAT: [1] Gang Liu, Apurv Puri and Sriram Neelamegham, Glycosylation Network Analysis Toolbox (GNAT): a MATLAB based environment for systems glycobiology, Bioinformatics 2013 29: 404-406 -
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VOC-DPM
Object detection system using deformable part models (DPMs)
...It implements both latent SVM training (where part assignments are treated as latent variables) and weak-label structural SVM (WL-SSVM) for learning from partially labeled data. The code integrates several enhancements: a star-cascade detection algorithm to speed up screening, context rescoring (re-ranking detections using contextual information), and various optimizations like in-memory training (rather than large on-disk data files). -
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Fast and multi platform reader of network traces, have possible to shared date in screen, file or Matlab
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C2Mat is a simple wrapper library that allows OpenCV data structures to be transferred between C++ and Matlab. It lets a program combine the speed of OpenCV with the power of Matlab.
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This project applies an interpretation of a k-NN algorithm to a library of GPS commuter data for speed prediction. The overall goal is to lay the foundation for a power management protocol for use in electric vehicles with hybrid energy storage.
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Tool for visualizing artificial neural networks in Matlab using the Matlab Neural Network Toolbox (see wiki for details).
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A collection of functions, in the end to be wrapped in a gui, that allow users to analyze networks from global (eigenvector centrality) and local (degree dist, statistical significance) perspectives. Implemented in matlab.
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Projeny (Probablistic Networks Generator in Java) is a graphical (Java SWT) front-end to BNT (Bayes Net Toolbox for Matlab). Projeny requires BNT, JMatLink and a Matlab back-end. There is no installable release package, but source code is available on SVN - please check out from SVN to use Projeny. Projeny was started with BNJ as the base.
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