Search Results for "classification" - Page 15

Showing 644 open source projects for "classification"

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  • 1
    LearningToCompare_FSL

    LearningToCompare_FSL

    Learning to Compare: Relation Network for Few-Shot Learning

    ...The core idea implemented here is the relation network, which learns to compare pairs of feature embeddings and output relation scores that indicate whether two images belong to the same class, enabling classification from only a handful of labeled examples. The repository provides training and evaluation code for standard few-shot benchmarks such as miniImageNet and Omniglot, making it possible to reproduce the experimental results reported in the paper. It includes model definitions, data loading logic, episodic training loops, and scripts that implement the N-way K-shot evaluation protocol common in few-shot research. ...
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  • 2
    favorites-web
    ...When you have more than 1,000 websites or articles in your browser's favorites, finding things is definitely a labor of life. Then let the cloud collection help you solve it, which is convenient for classification, organization, query and search. Cloud Collection is an open source website built with Spring Boot, which allows users to collect a website online anytime, anywhere, and categorize the collected websites or articles on the website, which can be used as temporary storage for later reading.
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  • 3
    PySptools

    PySptools

    Hyperspectral algorithms for Python

    A lightweight hyperspectral imaging library that provides developers with spectral algorithms for the Python programming language. New for v0.14.x: a scikit-learn bridge (alpha and partial). The functions and classes are organized by topics: * abundance maps: FCLS, NNLS, UCLS * classification: AbundanceClassification, NormXCorr, KMeans SAM, SID, SVC * detection: ACE, CEM, GLRT, MatchedFilter, OSP * distance: chebychev, NormXCorr, SAM, SID * endmembers extraction: ATGP, FIPPI, NFINDR, PPI * material count: HfcVd, HySime * noise: Savitzky Golay, MNF, whiten * sigproc: bilateral * sklearn: HyperEstimatorCrossVal, HyperSVC and others * spectro: convex hull quotient, features extraction (tetracorder style), USGS06 lib interface * util: load_ENVI_file, load_ENVI_spec_lib, corr, cov and others The library do an extensive use of the numpy numeric library and can achieve good speed. ...
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  • 4
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  • 5
    Convolutional Recurrent Neural Network

    Convolutional Recurrent Neural Network

    Convolutional Recurrent Neural Network (CRNN) for image-based sequence

    ...This hybrid approach allows the model to recognize sequences of characters directly from images without requiring explicit character segmentation. The implementation also integrates the Connectionist Temporal Classification (CTC) loss function, enabling end-to-end training of the model using labeled sequence data. CRNN has been widely used in computer vision tasks that require interpreting text embedded in images, such as reading street signs, documents, or natural scene text.
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  • 6
    file-sorter

    file-sorter

    It sorts your files fast and easily.

    This windows application helps you to sort your files easily. Classification of files sometimes turns into a big problem for users and they need to spend many times to find and sort the files. "File Sorter" program has made to solve this problem for windows users. It's a light and simple application that creates some directories (folders) for each group of files (based on their type) and move them to the proper directory.
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  • 7
    FS-Blog

    FS-Blog

    Personal blog, the pioneering work of Spring Boot,

    Personal blog, the pioneering work of Spring Boot, using Spring Boot + MyBatis, front-end Bootstrap + LayUI, supports the lightweight Markdown editor Editor.md favored by programmers, and supports tag classification retrieval. Core framework is SpringBoot, ORM framework is MyBatis, MyBatis toolis MyBatis Mapper, MVC frameworks is Spring MVC, Template engine is Freemarker, Compilation auxiliary plug-in: Lombok, CSS Framework is BootStrap 4.0, Markdown editor is Editor.md, and Database is MySQL
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  • 8
    DIGITS

    DIGITS

    Deep Learning GPU training system

    The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. DIGITS is completely interactive so that data scientists can focus on designing and training networks rather than programming and debugging. ...
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  • 9

    PressureEquipmentHazard

    Hazard classification of Pressure Equipment

    Hazard classification of Pressure Equipmenti on conformity to European directive 2014/68/UE, 97/23/CE (PED) or ASME BPVC
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  • 10
    Image classification models for Keras

    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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  • 11

    JSiteDescriptor

    Binding site descriptor generation for SVM based classification.

    A set of java programs that extract coordinate and chemical information from PDB files. The binding site regions are extracted using grid based scheme. For binding site, spatio-chemical descriptor is generated based on PocketMatch algorithm of Dr. Kalidas (author of this project too).
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  • 12
    Deeplearning-papernotes

    Deeplearning-papernotes

    Summaries and notes on Deep Learning research papers

    Deeplearning-papernotes is an implementation of Convolutional Neural Networks for sentence and text classification in TensorFlow, based on a well-known research paper that applies CNN architectures to natural language processing tasks with strong performance in sentiment analysis and similar classification problems. The repository provides the complete network definition, including an embedding layer to convert words into dense representations, convolution and max-pooling layers to extract informative features, and a final softmax classifier to distinguish between target classes. ...
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  • 13
    Keras resources

    Keras resources

    Directory of tutorials and open-source code repositories

    ...It aggregates a wide range of resources, including beginner guides, advanced tutorials, code examples, and third-party tools, all organized into a single reference hub. The repository covers diverse topics such as image classification, natural language processing, reinforcement learning, and generative models, providing both theoretical and practical insights. It also includes links to external projects built with Keras, demonstrating real-world applications of deep learning techniques. The structure is designed for easy navigation, allowing users to quickly find relevant materials based on their skill level or area of interest. ...
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  • 14
    Five video classification methods

    Five video classification methods

    Code that accompanies my blog post outlining five video classification

    ...So a 41-frame video and a 500-frame video will both be reduced to 40 frames, with the 500-frame video essentially being fast-forwarded. We won’t do much preprocessing. A common preprocessing step for video classification is subtracting the mean, but we’ll keep the frames pretty raw from start to finish.
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  • 15

    DGRLVQ

    Dynamic Generalized Relevance Learning Vector Quantization

    ...Dynamic-GRLVQ (DGRLVQ), which adapts the model complexity to the given problem during training by adding or removing prototypes dynamically/realtime one by one for each category until satisfactory classification results are achieved.
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  • 16

    fscaret_shiny

    UI for fscaret

    User Interface (ui) application which implements the automated feature selection provided by the 'fscaret' package of R-environment.
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  • 17
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  • 18
    EasyPR

    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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  • 19

    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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  • 20
    Accord.NET Framework

    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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  • 21
    Neural Network signal recognition rtlsdr

    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
    Downloads: 5 This Week
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  • 22
    Clus
    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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  • 23
    R-FCN

    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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  • 24
    MYRA

    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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    Downloads: 5 This Week
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  • 25
    libfastknn

    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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