Search Results for "void based linux" - Page 2
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Showing 48 open source projects for "void based linux"
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OSVIACAM
OSVIACAM Linux for quadriplegic disabled
OSVIACAM is a linux image based on openSUSE aimed at quadriplegic disabled. The image is in beta, but features the key features to meet the need to operate an operating system without mouse and keyboard. The differential of the image is to rely on the application VIACAM that allows to move the mouse with only the movements of the face. -
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Portable Robotics Eye Vergence Control
Eye movements control portable on different robotic stereo heads
This project provides a software module for the control of the binocular coordination of a robotic stereo head, based on a bio-inspired algorithm. The project is now available for the iCub platform to work on YARP [https://github.com/stino78/vergence-control/][1] The algorithm works on the top of a distributed representation of binocular disparity supplied by a population of binocular energy-model neural units. The project allows a robust control and adaptive binocular coordination... -
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ECO
Matlab implementation of the ECO tracker
ECO (Efficient Convolution Operators for Tracking) is a high-performance object tracking algorithm developed by Martin Danelljan and collaborators. It is based on discriminative correlation filters and designed to handle appearance changes, occlusions, and scale variations in visual object tracking tasks. The code provides a MATLAB implementation of the ECO and ECO-HC (high-speed) variants and was one of the top performers on multiple visual tracking benchmarks. -
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R-FCN
R-FCN: Object Detection via Region-based Fully Convolutional Networks
R-FCN (“Region-based Fully Convolutional Networks”) is an object detection framework that makes almost all computation fully convolutional and shared across the image, unlike prior region-based approaches (e.g. Faster R-CNN) which run per-region sub-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... -
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HashingBaselineForImageRetrieval
Various hashing methods for image retrieval and serves as the baseline
This repository provides baseline implementations of deep supervised hashing methods for image retrieval tasks using PyTorch. It includes clean, minimal code for several hashing algorithms designed to map images into compact binary codes while preserving similarity in feature space, enabling fast and scalable retrieval from large image datasets. -
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reacTIVision is a computer vision framework for the fast and robust tracking of markers attached on physical objects, and the creation of multi-touch surfaces. It was designed for the rapid development of table-based tangible user interfaces.
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Netvlad
NetVLAD: CNN architecture for weakly supervised place recognition
NetVLAD is a deep learning-based image descriptor framework developed by Relja Arandjelović for place recognition and image retrieval. It extends standard CNNs with a trainable VLAD (Vector of Locally Aggregated Descriptors) layer to create compact, robust global descriptors from image features. This implementation includes training code and pretrained models using the Pittsburgh and Tokyo datasets. -
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...The framework was mainly designed as a toolkit for the rapid development of interactive art projects that explore dynamics of complex environments. The Scene GUI runs and compiles under Windows, Linux, and MacOS X, and is available in both 32 bit and 64 bit versions.
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TSPS
TSPS is an open toolkit for sensing people in spaces.
The Toolkit for Sensing People in Spaces (TSPS) is an open-source tool for creating interactive applications based on natural user interaction. It wraps computer vision algorithms into a simple, easy-to-use interface. TSPS was developed in openFrameworks for use in design, prototyping, and installed systems. We use TSPS for retail, fine arts installations, rapid prototyping, educational workshops, and provide the source openly for use in production. It builds on the backs of giants and... -
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road-scene-understanding
A dataset for road scene understanding.
Autonomous driving is gaining increasing attention in the computer vision research community, as vision based scene understanding is key to self-driving cars. In this web page, we make image datasets public for the purpose of furthering research in scene understanding. -
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Awesome Recurrent Neural Networks
A curated list of resources dedicated to RNN
A curated list of resources dedicated to recurrent neural networks (closely related to deep learning). Provides a wide range of works and resources such as a Recurrent Neural Network Tutorial, a Sequence-to-Sequence Model Tutorial, Tutorials by nlintz, Notebook examples by aymericdamien, Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow, Keras (Tensorflow / Theano)-based modular deep learning library similar to Torch, char-rnn-tensorflow by sherjilozair, char-rnn... -
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Rcnn
R-CNN: Regions with Convolutional Neural Network Features
This repository contains the original MATLAB implementation of R-CNN (Regions with Convolutional Neural Networks), a pioneering deep learning-based object detection framework. Developed by Ross Girshick, R-CNN combines region proposals with convolutional neural networks to detect objects in images. It was one of the first approaches to significantly improve performance on object detection benchmarks like PASCAL VOC. -
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Levo
Application to annotate objects and events in videos and pictures.
This software allows to label events in videos (e.g. phoning, hand-shaking,...) and objects in images (e.g. person, car,...). The annotation of events and objects are saved into XML files and can be used for training and/or testing computer vision algorithms. In particular, LEVO can visualize and write PASCAL VOC-compatible annotation files. Some annotations from LABEL ME can be read as well. It has been tested on MS Windows. However, since it is Java-based code, it should works on... -
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VOSM2DExplorer
VOSM 2D Explorer
An Eclipse SWT Java GUI based application to demonstrate 2D statistical models in computer vision, for face representation. -
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Bluetooth MeyMouse Accelerometer camera
J2me Accelerometer Camera light based over Bluettooth over mobile
J2me Accelerometer Camera light based over Bluettooth over mobile phone (Turn Your Old j2me Phone become slick accelerometer camera based MOUSE over bluetooth great for develope accelerometer camera based game Zzzzzzzz -
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Time Adaptive Self-Organizing Map
An Artificial Neural Network for Clustering, Classification, etc
This project tries to include Time Adaptive Self-Organizing Map (TASOM) implementations for solving Computational Intelligence problems such as Pattern Recognition, Computer Vision, Clustering, Active Contour Modeling, and the like. The TASOM has been originally introduced for adaptive and changing environments. Several versions of TASOM networks have been introduced. Some of them are capable of changing the number of neurons based on the problems at hand. Moreover, a binary tree version... -
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Web-based software to label objects in digital images for creating datasets for computer vision research.
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A photo gallery management system based on hand gesture recognition. You must make three color markers by yourself, which the red one on index of the right hand, the green one on thumb of the right hand and the blue one on index of the left hand.
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Diglo is a Music Information Retrieval System based on Computer Vision and Audio Spectrum Analysis, using algorithmic operations to find emergent patterns in musical performance. Also it functions as a low-cost Motion Capture Analysis system.
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CVSharp (aka Computer Vision in C#) is a Computer Vision project. Until the present day just one part of the whole project was actually developed. It's called CVSharp Lab, an Image Processing Tool.
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GPUVision is a framework for creating GPU based general purpose programs, image processing programs, and computer vision programs in C++. Supported libraries include matrix operations, graph partitioning, kernels, corner detection, edge detection etc.
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