Search Results for "classification" - Page 15
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Showing 576 open source projects for "classification"
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EasyPR
An easy, flexible, and accurate plate recognition project
...The system is designed to work in unconstrained environments, meaning it can handle images with varying lighting conditions, perspectives, and backgrounds. Its architecture includes multiple stages such as plate localization, character segmentation, and character classification to achieve accurate recognition results. -
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FSM: Font System Manager
FSM is a tool designed to bridge the gap between ImageMagick & paperjs
...This makes it difficult to reproduce accurately effects, for example, in video projects where the placement of text, sub-images, etc needs to be tested before production. While paperjs will render a scene in a browser context, it cannot be used in production, where ImageMagick is necessary. FSM allows for the classification of usable fonts for both these interfaces, accurate measurement of font dimensions such as descender, bearing, and extended bearing, and the means for translating between the differing font description systems used. This script which requires: *PHP >= 7.0 *MySQL >= 5.6 *ImageMagick >= 6.9, Imagick for PHP Paperjs and jquery are bound in via CDN. ... -
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Accord.NET Framework
Machine learning, computer vision, statistics and computing for .NET
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and extensive documentation and a wiki help fill in the details. The Accord.NET project provides... -
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Neural Network signal recognition rtlsdr
Deep learning signal classification (recognition) using rtl-sdr dongle
WARNING: Outdated version here. Everything has been moved to github: https://github.com/randaller/cnn-rtlsdr -
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Clus is an open source machine learning system that implements predictive clustering trees (PCTs) and predictive clustering rules (PCRs). PCTs generalize traditional classification and regression trees by altering the heuristic that is used to constr
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Learning to Learn in TensorFlow
Learning to Learn in TensorFlow
...The repository provides code for training and evaluating learned optimizers that can generalize across different problem types, such as quadratic functions and image classification tasks (MNIST and CIFAR-10). Using TensorFlow, it defines a meta-optimizer model that learns by observing and adapting to the optimization trajectories of other models. The project allows users to compare performance between traditional optimizers and the learned optimizer (L2L) on various benchmarks, demonstrating how optimization strategies can be learned through experience. ... -
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R-FCN
R-FCN: Object Detection via Region-based Fully Convolutional Networks
...The repository provides an implementation (in Python) supporting end-to-end training and inference of R-FCN models on standard datasets. The authors propose position-sensitive score maps to reconcile the need for translation variance (in detection) and translation invariance (in classification). R-FCN is efficient (low per-region overhead) and competitive in accuracy (e.g. with ResNet backbones). Position-sensitive score maps for per-region classification without expensive per-region convs. Optional “deformable R-FCN” extension for improved performance. -
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MYRA
A collection of ACO algorithms for the data mining classification task
MYRA is a collection of Ant Colony Optimization (ACO) algorithms for the data mining classification task. It includes popular rule induction and decision tree induction algorithms. The algorithms are ready to be used from the command line or can be easily called from your own Java code. They are build using a modular architecture, so they can be easily extended to incorporate different procedures and/or use different parameter values. -
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libfastknn
Fast C++ KNN classifier
KNN Classifier library for C++, at background using armadillo. In k-NN classification, the output is a class membership. An object is classified by a majority vote of its neighbors, with the object being assigned to the class most common among its k nearest neighbors (k is a positive integer, typically small). If k = 1, then the object is simply assigned to the class of that single nearest neighbor. -
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...Finally, the phase data from 1D Log-Gabor filters was extracted and quantized to four levels to encode the unique pattern of the iris into a bit-wise biometric template. The Hamming distance was employed for classification of iris templates, and two templates were found to match if a test of statistical independence was failed.
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
...The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. The repository contains reference code accompanying the research paper node2vec: Scalable Feature Learning for Networks (KDD 2016). It allows researchers and practitioners to apply node2vec to various graph datasets and evaluate embedding quality on downstream tasks. By bridging ideas from graph theory and word embedding models, this project demonstrates how graph-based machine learning can be made efficient and flexible. -
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...The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. -
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This program presents `DIABDIAG', helps to classify the patients with diabetes of T2DM in two types, who are asymptomatic and symptomatic. DIABDIAG uses the principle of Diagnosis Algorithm to sort patients asymptomatic and symptomatic. The classification of two types is used main and sub-main factors that can help to decide under which type the patients should be. DIABDIAG uses as I mention Diagnosis Algorithm by asking users to enter and answer some question then it gives them the result of classifying with advice.
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JCLTP
A Java Class Library for Text Processing
...JCLTP is distributed under the GNU license. It incorporates several technologies that enable process information while applying AI techniques, in order to build predictive models for text classification. Through a flexible structure of interfaces and classes, the opportunity to extend, adapt and add functionality JCLTP is provided. Thus, analysis of new types of information is much easier and intuitive. The researcher can use the class library by adding it to his project or direct through specific commands created for these cases. ... -
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EpiMINE
program for mining epigenomic data
EpiMINE is a program designed for mining epigenomic data. This application performs genome wide based quantitative and correlative analysis between different annotated or raw chip-seq like datasets in the regions of interest (RI). Apart from this the tool takes the advantage in linking results with expression data. It is available both in graphical user interface and in command line form. It can be executed in Mac and Linux platforms. Dependencies: python >= 2.7 version python... -
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Python Machine Learning book
The book code repository and info resource
What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning. From theory to the actual code that you can directly put into action! This is not yet just another "this is how scikit-learn works" book. I aim to explain all the underlying concepts, tell you everything you need to know in terms of best practices and caveats, and we will put those concepts into action mainly using NumPy, scikit-learn, and Theano. This is not... -
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Random Bits Regression
Random Bits Regression is a strong general predictor.
We proposed an accurate, robust and fast general predictor (RBR) for regression and classification in big data era. The application of this method is very broad, from science to industry, finance and health. The accuracy and robustness improvement of our method over existing method could bring huge benefits in some critical applications. For example, natural disaster prediction, stock price prediction, personal/population disease prediction. -
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Statuspage
A statuspage generator that lets you host your statuspage for free
Statuspage is an open-source status page generator that enables teams to publish service health dashboards directly from GitHub infrastructure. The tool automatically converts GitHub issues into incident reports and uses labels to represent severity levels, allowing teams to manage incident communication through familiar workflows. It is designed to be hosted for free on GitHub Pages, making it especially attractive for startups and open-source projects that want transparent uptime... -
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FOCUS2
FOCUS2: agile metagenomic classificication using reduced DB
Summary: Metagenomics approaches rely on identifying the presence of organisms in the microbial community from a set of unknown DNA sequences. Sequence classification has valuable applications in multiple important areas of medical and environmental research. Here we introduce FOCUS2, an update of the previously published computational method FOCUS. FOCUS2 was tested with 10 simulated and 543 real metagenomes demonstrating that the program is more sensitive, faster, and more computationally efficient than existing methods -
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GUI Ant-Miner is a tool for extracting classification rules from data. It is an updated version of a data mining algorithm called Ant-Miner (Ant Colony-based Data Miner).
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ReLiS
Tool for conducting systematic literature reviews and studies
...ReLiS is a tool that helps him considerably reduce the effort to analyze the corpus of papers, typically varying between hunderds and thousands depending on the research topic. ReLiS allows the user to follow a systematic process and automate the classification of papers as much as possible during the literature study. -
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CDSS for Allergy-Diagnosis
A clinical Decision Support System for Diagnosis of Allergic Rhinitis
A Clinical Decision Support System (CDSS) can be used for diagnosing allergic disorders. CDSS with rule based classification approaches, aid junior doctors and clinicians to diagnose and make reliable decisions. The results of an intradermal skin test is the input to the CDSS. The System predicts the presence or absence of ALLERGIC RHINITIS. The system is tailored to suit to the common allergens (inhalents and ingestants) prevalent in Chennai, South India. -
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GMaVis: A DSL for Geo-Visualization
It is a domain-specific language for large data geo-visualizations
GMaVis is an external domain-specific language (DSL) that facilitates the creation of visualization of geospatial information by using multi-core architectures to process data in parallel. Its compiler abstracts complexities from the whole visualization creation process, even in the data pre-processing phase. Also, it allows domain users with low-level knowledge in computer programming to create these visualizations through a high-level description language. These users can easily do it with...
