Search Results for "source code computer" - Page 55
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Showing 1666 open source projects for "source code computer"
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Bottery
A conversational agent prototyping platform
Bottery is a prototyping environment and mini-language for designing conversational agents as explicit state machines rather than opaque bundles of code. It encourages authors to model intents, dialog turns, and transitions in a compact, declarative form that’s easy to visualize and simulate. A built-in simulator lets you “play” the conversation, test edge cases, and tweak flows without wiring up back-end services first. Because behavior is defined in a DSL, teams can version the... -
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WarriorJS
JavaScript coding game where players program a warrior to win battles
WarriorJS is an educational programming game designed to teach and challenge JavaScript skills through interactive gameplay. In the game, players control a warrior who must climb a tower filled with enemies, captives, and obstacles in pursuit of a legendary JavaScript Sword located at the top. Each floor of the tower presents a new challenge that requires players to write JavaScript code to instruct the warrior on how to move, fight enemies, rescue captives, and safely reach the stairs to... -
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The GAN Zoo
A list of all named GANs
...The list includes references to many GAN variants along with links to their original research papers and sometimes implementation code. Users can browse the dataset or explore a tabular version that allows filtering by year or searching for specific model names. The repository encourages contributions from the community so that newly published GAN architectures can be added to the list. -
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Delphi Face Detection
Delphi face detection
...Runs on Windows XP to Windows 10 Available on MsAcceSS or SQLite Dataface! Depending on Request! You can reprogram / setup / configure / scale the Face Recognition accuracy! C++Builder Face Detection: FREE Source code! https://sourceforge.net/projects/cbuilder-opencv-face-detection/ C++Builder Face Recognition: https://sourceforge.net/projects/c-builder-face-recognition/ Technical Support is always online, thank you -
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Skater
Python library for model interpretation/explanations
...Model interpretation is the ability to explain and validate the decisions of a predictive model to enable fairness, accountability, and transparency in algorithmic decision-making. The library has embraced object-oriented and functional programming paradigms as deemed necessary to provide scalability and concurrency while keeping code brevity in mind. -
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LearningToCompare_FSL
Learning to Compare: Relation Network for Few-Shot Learning
LearningToCompare_FSL is a PyTorch implementation of the “Learning to Compare: Relation Network for Few-Shot Learning” paper, focusing on the few-shot learning experiments described in that work. 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... -
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OpenCE
Contrast Enhancement Techniques for low-light images
...The repository includes training scripts, pretrained models, and testing code, allowing users to reproduce results reported in the paper. It supports standard human pose estimation benchmarks such as COCO, with configurations optimized for accuracy and efficiency. As an open resource, OpenCE offers researchers and practitioners a strong baseline for pose estimation and a foundation for extending CPN-based methods. -
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Generative Models
Collection of generative models, e.g. GAN, VAE in Pytorch
This project is a comprehensive open-source collection of implementations of various generative machine learning models designed to help researchers and developers experiment with deep generative techniques. The repository contains practical implementations of well-known architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Restricted Boltzmann Machines, and Helmholtz Machines, implemented primarily using modern deep learning frameworks like PyTorch... -
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The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function.
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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php-text-generator
Fast SEO text generator on a mask
Fast SEO text generator on a mask. Written in PHP. I do not use regular expressions and the fastest. I covered tests and simple! Supporting recursive text generation rules. It supports multiple encodings. This package implements the functionality of a similar package for Go Lang. It supports multiple encodings. Supporting recursive text generation rules. Fast! Does not use regular expressions. Easy wrapping thanks to the integrated interface. Covered tests. Written by PSR standards and 100%... -
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MatlabFunc
Matlab codes for feature learning
...The project is intended to provide reusable and adaptable MATLAB code that can save time for researchers and students working on experimental or applied projects. By consolidating these tools in one place, MatlabFunc serves as a practical reference and toolkit for both academic and engineering purposes. Contributions and improvements from the community are encouraged, allowing the repository to grow into a richer resource over time. -
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VideoMan Library
C++ library for image acquisition and visualization
Library for capturing video from cameras, 3d sensors, frame-grabbers, video files and image sequences. It can also display multiple images using OpenGL with different layouts. Easy integration with OpenCV, CUDA... Perfect for computer vision. Keywords: video capture, computer vision, machine vision, opencv, opengl, cameras, video input devices, firewire, usb, gige -
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Deep Reinforcement Learning TensorFlow
TensorFlow implementation of Deep Reinforcement Learning papers
Deep Reinforcement Learning TensorFlow is a comprehensive TensorFlow codebase that implements several foundational deep reinforcement learning algorithms for educational and experimental use. The repository focuses on clarity and modularity so users can study how different RL approaches are built and compare their behavior across environments. It includes implementations of well-known algorithms such as Deep Q-Networks (DQN), policy gradients, and related variants, demonstrating how neural... -
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Convolutional Recurrent Neural Network
Convolutional Recurrent Neural Network (CRNN) for image-based sequence
Convolutional Recurrent Neural Network provides an implementation of the Convolutional Recurrent Neural Network (CRNN) architecture, a deep learning model designed for image-based sequence recognition tasks such as optical character recognition and scene text recognition. The architecture combines convolutional neural networks for extracting visual features from images with recurrent neural networks that model sequential dependencies in the extracted features. This hybrid approach allows the... -
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SSD Keras
A Keras port of single shot MultiBox detector
This is a Keras port of the SSD model architecture introduced by Wei Liu et al. in the paper SSD: Single Shot MultiBox Detector. Ports of the trained weights of all the original models are provided below. This implementation is accurate, meaning that both the ported weights and models trained from scratch produce the same mAP values as the respective models of the original Caffe implementation. The main goal of this project is to create an SSD implementation that is well documented for those... -
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Show Facebook Computer Vision Tags
Chrome Extension that displays automated image tags from Facebook
Show Facebook Computer Vision Tags is a Chrome (and Firefox) browser extension created to expose and overlay the automatically generated image tags that Facebook applies to photos in users’ feeds. Since Facebook uses a computer-vision model to analyse user-uploaded images and generate alt-text tags for accessibility (e.g., “Image may contain: golf, grass, outdoor and nature”), this extension surfaces those hidden tags directly in the UI—revealing what kind of information Facebook infers... -
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stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course
This repository contains code examples for the course CS 20: TensorFlow for Deep Learning Research. It will be updated as the class progresses. Detailed syllabus and lecture notes can be found in the site. For this course, I use python3.6 and TensorFlow 1.4.1. -
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NOMAD is a C++ code that implements the MADS algorithm (Mesh Adaptive Direct Search) for difficult blackbox optimization problems. Such problems occur when the functions to optimize are costly computer simulations with no derivatives.
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IGVC IITK Data
Data useful for testing autonomous navigation algorithms
This repository is only used for the purpose of dataset storage for Team IGVC, IITK. For the relevant code, see our GitHub repositories. (https://github.com/igvc-iitk). The recorded data is used for testing various algorithms related to Computer Vision, SLAM, Motion Planning etc. -
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PanoramaServer
Open Source Panorama Server for free virtual tour of 360 degrees views
...If made available online to general public over the internet, can even share the link of your virtual trips. PanoramaServer is free as it is open source licensed. -
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EvalAI
Evaluating state of the art in AI
EvalAI is an open-source platform for evaluating and comparing machine learning (ML) and artificial intelligence (AI) algorithms at scale. We allow the creation of an arbitrary number of evaluation phases and dataset splits, compatibility using any programming language, and organizing results in both public and private leaderboards. Certain large-scale challenges need special computing capabilities for evaluation. -
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mAP
Evaluates the performance of your neural net for object recognition
In practice, a higher mAP value indicates a better performance of your neural net, given your ground truth and set of classes. The performance of your neural net will be judged using the mAP criteria defined in the PASCAL VOC 2012 competition. We simply adapted the official Matlab code into Python (in our tests they both give the same results). First, your neural net detection-results are sorted by decreasing confidence and are assigned to ground-truth objects. We have "a match" when they... -
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OpenPR stands for Open Pattern Recognition project and is intended to be an open source library for algorithms of image processing, computer vision, natural language processing, pattern recognition, machine learning and the related fields.
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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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'...
