Search Results for "computer based training" - Page 2
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163 projects for "computer based training" with 2 filters applied:
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Official YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art
YOLOv7 is the official implementation of the paper “YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.” It is a PyTorch-based object detection project focused on high speed and strong accuracy for real-time computer vision. The repository provides model definitions, training scripts, testing tools, inference examples, pretrained weights, and deployment-oriented materials. YOLOv7 introduced training-time improvements that raise accuracy without increasing inference cost, which is why the project became important in real-time detection research. ... -
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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
...The project added multi-GPU training, target count statistics, learning rate scheduling with step and cosine options, and optimizer selection between Adam and SGD. It also includes adaptive learning rate adjustment based on batch size, image cropping, many configurable parameters, and expanded comments for easier study. It is well suited for learners and developers who want a hands-on YOLOv3 codebase in PyTorch. -
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DeepLabv3 Plus
Encoder-Decoder with Atrous Separable Convolution
...The project also supports multi-GPU training, multiple backbones, learning rate schedules with step and cosine options, optimizer selection, and adaptive learning rate behavior based on batch size. It is useful for users who want a stronger semantic segmentation baseline than U-Net for scene-level segmentation tasks. -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature extractors. ... -
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Model Search
Framework that implements AutoML algorithms
Model Search is an AutoML research system for discovering neural network architectures with minimal human intervention. Instead of hand-crafting models, you define a search space and objectives, then the system explores candidate architectures using controllers and population-based strategies. It supports multiple tasks (such as vision or text) by letting you express reusable building blocks—layers, cells, and topologies—that the search can recombine. Training, evaluation, and promotion of candidates are orchestrated automatically, with strong emphasis on reproducibility and fair comparisons. The framework logs trials, metrics, and artifacts so you can analyze what the search learned and why certain designs dominate. ... -
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Flux3D.jl
3D computer vision library in Julia
Flux3D.jl is a 3D vision library, written completely in Julia. This package utilizes Flux.jl and Zygote.jl as its building blocks for training 3D vision models and for supporting differentiation. This package also have support of CUDA GPU acceleration with CUDA.jl. -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
...Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. The repository includes all necessary scripts for training, dataset preparation, distributed training, evaluation, and audio separation. -
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Automatic Drawing Generation
A canvas library for generating technical drawings
The ADG library (Automatic Drawing Generation) is a set of functions focused on automating the drawing of mechanical parts. It is not a CAD system but a GObject-based library where a custom application can put common CAD entities such as paths, hatches and dimensions, to automatically create technical drawings. A demo application is provided in order to show the capabilities of the canvas. Although it is possible to interact with the library directly in C (that is what the adg-demo... -
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YOLOR
implementation of paper - You Only Learn One Representation
...The project focuses on object detection while exploring how a shared representation can support multiple tasks. It builds on the YOLO family and related PyTorch detection work, combining practical detector training with a research idea about unified representations. YOLOR includes model configurations, training code, evaluation scripts, inference tools, and pretrained weights. Its central contribution is the use of implicit knowledge to improve network performance without treating every task as fully separate. It is useful for computer vision researchers and developers studying YOLO-style detectors, representation learning, and high-performance detection systems. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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ReinventCommunity
Jupyter Notebook tutorials for REINVENT 3.2
This repository is a collection of useful jupyter notebooks, code snippets and example JSON files illustrating the use of Reinvent 3.2. -
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4WS.Platform
Development Platform for Web and Mobile Applications
This RAD platform allows to quickly develop web and mobile applications without any coding task. Applications can be developed by simply configuring them through a graphical environment. There is no limit in the complexity of the applications to create, since there is always the chance to include custom scripts made by a developer. The platform supports multiple databases and operating systems, since it has been developed using Java and it provides a rich user interface based on Sencha ExtJS. -
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USE is a system for the specification and validation of information systems based on a subset of the Unified Modeling Language (UML) and the Object Constraint Language (OCL). Please report any encountered bugs using the ticket system. The USE documentation can be found on the project homepage linked below. Downloads for the most popular plugins can be found here: http://sourceforge.net/projects/useocl/files/Plugins/
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Albedo
A recommender system for discovering GitHub repos
Albedo is an open-source recommender system aimed at helping developers discover GitHub repositories by learning from activity signals. It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible... -
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The Object-Role Modeling (ORM) standard version 2, associated schemas and generation tools, and a reference implementation in the form of the Natural Object-Role Modeling Architect for Visual Studio (NORMA) product.
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phpexplorator is a web interface to remote explore, manage, preview , edit, create, copy, rename, download, upload, zip, unzip ..etc, files, images, and directory in the server site. Integrated with TinyMce, useful for computer programmer and admin.
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Face-Detection-JavaScript
Small browser-based computer vision demo
Face-Detection-JavaScript is a small browser-based computer vision demo that uses JavaScript and face-api.js to analyze live webcam video. It loads face detection, facial landmark, face recognition, and facial expression models from a local models folder. Once the webcam stream starts, the app creates a canvas overlay and draws detection results directly over the video feed. It can identify face boxes, map facial landmark points, and display detected expressions in near real time. ... -
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ObjectBuilder2
C++ CASE tool, full life cycle code generator
ObjectBuilder is a C++ code generation CASE tool (CASE, code generation, refactoring, documentation generation). It lets you create, manipulate and navigate classes, class relations, class members and class methods at a high level of abstraction. ObjectBuilder dramatically simplify work with C++ project architecture. I use it and think that tree OO interface targeted to C++ more fast and power than UML class diagrams. ObjectBuilder perfectly organize C++ header files with any level of... -
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This Project will administer an exam on an applet using 4 answer mutliple choice questions. Only one answer may be selected per question. Later we may improve this but for now this is the scope. We will use XML to read and write exams.
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This will be a simple tandem text editor. It will broad cast document events to clients over a web connection. What it should do is allow more than one person to edit a document at the same time. Of course the one editing has a lock.
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Requirements management tool designed to achieve full SDLC traceability for features, requirements, design, implementation and testing. UI for requirements derivation, version control, attributes etc. Upgrade path also available at https://sourceforge.net/projects/nimble
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TreeGraph
Information Manager(split/analyze/compare/combine).
For Homepage, Blog, Family Tree, Database, C#|hjt|js|chm Editor. Convert hjt2xml, (c#)cs2xml, chm2xml, js2xml, xml2cs, xml2js, xml2hjt, cs2hjt, hjt2cs, cs2chm, hjt2chm. IE/Opera/Firefox/PocketPC supported. -
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MPL Bytecode Compiler
Micro Programming Language - A Portable Language for Micro Computers
...No more language changes are to be made. The compiler is complete and should be easy to translate to other languages if you so choose. MPL is a small, simple language based on BCPL, B, C and Jesusonic. The compiler and interpreter are written in portable Pascal. I have successfully compiled MPL for CP/M, DOS, Windows, Atari ST, Amiga and the Tandy Colour Computer. MPL is designed to be tiny in every way, while implementing all the important features of BCPL & B. The result is a compiler written in a high level language (PASCAL) which compiles to under 16K (CP/M). ... -
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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. The project includes scripts for training, evaluation, and data handling, making it easy to run experiments on datasets such as movie reviews or other labeled text collections. ... -
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Gin Config
Gin provides a lightweight configuration framework for Python
Gin Config is a lightweight and flexible configuration framework for Python built around dependency injection. It enables developers to manage complex parameter hierarchies—particularly common in machine learning experiments—without relying on boilerplate configuration classes or protos. By decorating functions and classes with @gin.configurable, Gin allows their parameters to be overridden using simple configuration files (.gin) or command-line bindings. Users can define default parameter... -
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Deeplearning-papernotes
Summaries and notes on Deep Learning research papers
...It includes data preprocessing helpers, training scripts, and configuration options so developers can experiment with different filter sizes, dropout rates, and hyperparameters to optimize performance for their dataset.