Search Results for "classification" - Page 14
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Showing 641 open source projects for "classification"
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Tagstoo
Software to tag folders and files, with multimedia and epubs preview.
Tag folders and files (including multimedia) by dragging the tags on them, you can create tags of various shapes and colors for a more intuitive classification. Precise search possibilities, with various input fields, allowing to add all the necessary tags that you want. For example, in one field you can add the tags ‘cat' and 'white' and in another field you can add the tags 'dog' and 'brown', so the search result will return all white cats and brown dogs. You can also indicate that the folders where they are must have certain tags. ... -
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MIT Deep Learning
Tutorials, assignments, and competitions for MIT Deep Learning
...The repository provides hands-on tutorials that introduce the fundamental concepts behind neural networks, deep learning architectures, and modern machine learning techniques. Many of the tutorials include practical implementations that demonstrate tasks such as image classification, generative models, and neural network training workflows. The materials are structured as Jupyter notebooks so that learners can interact with the code and experiment with models while studying the concepts. The repository is designed to complement academic coursework and often evolves as new course material is developed. Because the tutorials are designed for educational use, they emphasize clear explanations and step-by-step demonstrations of deep learning concepts. -
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Omniglot
Omniglot data set for one-shot learning
...It includes both MATLAB and Python starter scripts (e.g. demo.m, demo.py) to illustrate how to load the images and stroke sequences and run baseline experiments (such as classification by modified Hausdorff distance). The dataset provides both an image representation of each character and the time-ordered stroke coordinates ([x, y, t]) for each instance. Includes stroke data (time-sequenced coordinates) per sample. The repository is intended as a benchmark dataset in few-shot / meta-learning research, not as a plug-and-play detection or classification engine. ... -
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ConvNet Burden
Memory consumption and FLOP count estimates for convnets
convnet-burden is a MATLAB toolbox / script collection estimating computational cost (FLOPs) and memory consumption of various convolutional neural network architectures. It lets users compute approximate burdens (in FLOPs, memory) for standard image classification CNN models (e.g. ResNet, VGG) based on network definitions. The tool helps researchers compare the computational efficiency of architectures or quantify resource needs. Estimation of memory consumption (e.g. feature map sizes, parameter storage). Support for multiple network definitions/architectures. Estimation of memory consumption (e.g. feature map sizes, parameter storage). ... -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo... -
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OCW Test - Out of Commerce Works
Program for out of commerce works detection
The OCW Test program has been designed to provide assistance in the detection of works outside trade, taking as reference a list of works from a specific bibliographic catalog. In this first version, the program operates on the identifiers of the books of the library of the Complutense University of Madrid. However, the program can be reedited, to work on any bibliographic catalog. -
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BossSensor
Hide screen when boss is approaching
BossSensor is an experimental open-source application that uses computer vision and machine learning to detect when a specific person, such as a supervisor or manager, approaches a computer workstation. The project uses a webcam to continuously capture images and analyze them using a face classification model trained to distinguish between the designated “boss” and other individuals. When the system detects that the trained face appears in the camera view, the program automatically triggers actions such as hiding the user’s screen or switching to a safe display. The software relies on libraries such as OpenCV, TensorFlow, and Python-based machine learning tools to perform face detection and classification. ... -
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Oryx
Lambda architecture on Apache Spark, Apache Kafka for real-time
Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, but with specialization for real-time large-scale machine learning. It is a framework for building applications but also includes packaged, end-to-end applications for collaborative filtering, classification, regression and clustering. The application is written in Java, using Apache Spark, Hadoop, Tomcat, Kafka, Zookeeper and more. Configuration uses a single Typesafe Config config file, wherein applications configure an entire deployment of the system. This includes implementations of key interface classes which implement the batch, speed, and serving logic. ... -
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Simd
High performance image processing library in C++
...It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. The algorithms are optimized with using of different SIMD CPU extensions. In particular the library supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. ... -
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TensorImage
Image classification library for easily training and deploying models
...Moreover, TensorImage can also be used to classify on thousands of images with trained image classification models. -
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Machine learning Resources
Some learning materials and research introduction on machine learning
...It serves as a curated knowledge base that introduces fundamental algorithms and techniques used in modern machine learning systems. The repository organizes materials that cover topics such as classification algorithms, neural networks, feature engineering, and model evaluation. Many sections reference research papers, tutorials, and open-source implementations that allow users to explore specific machine learning methods in greater depth. The project is maintained by researcher Jindong Wang, whose work focuses on machine learning research areas including transfer learning, domain adaptation, and robust learning methods. -
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apache spark data pipeline osDQ
osDQ dedicated to create apache spark based data pipeline using JSON
This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to... -
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cnn-text-classification-tf
Convolutional Neural Network for Text Classification in Tensorflow
The cnn-text-classification-tf repository by Denny Britz is a well-known educational implementation of convolutional neural networks for text classification using TensorFlow, aimed at helping developers and researchers understand how CNNs can be applied to natural language processing tasks. Based loosely on Kim’s influential paper on CNNs for sentence classification, this codebase demonstrates how to preprocess text data, convert words into learned embeddings, and apply multiple convolution filters to extract n-gram features that are then pooled and fed into a classifier. ... -
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Mixup-CIFAR10
mixup: Beyond Empirical Risk Minimization
mixup-cifar10 is the official PyTorch implementation of “mixup: Beyond Empirical Risk Minimization” (Zhang et al., ICLR 2018), a foundational paper introducing mixup, a simple yet powerful data augmentation technique for training deep neural networks. The core idea of mixup is to generate synthetic training examples by taking convex combinations of pairs of input samples and their labels. By interpolating both data and labels, the model learns smoother decision boundaries and becomes more... -
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Scidb
Chess Database Application
Scidb is an open-source chess database application for Windows, Unix/Linux. It is a new development inspired by Scid. -
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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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PyTom
http://www.sciencedirect.com/science/article/pii/S1047847711003492
PyTom is a toolbox developed for interpreting cryo electron tomography data. All steps from reconstruction, localization, alignment and classification are covered with standard and improved methods. Please sign up to our mailing list to keep up with the most recent updates and versions. -
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...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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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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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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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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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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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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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'...
