Search Results for "iperf-3"

MTCNN_face_detection_alignment is an implementation of the “Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks” algorithm. The algorithm uses a cascade of three convolutional networks (P-Net, R-Net, O-Net) to jointly detect faces (bounding boxes) and align facial landmarks in a coarse-to-fine manner, leveraging multi-task learning. Non-maximum suppression and bounding box regression at each stage. The repository includes Caffe / MATLAB code, support scripts, and instructions for dependencies. ...

...The tool requires as input the original RGB images, and the FastRed, FastBlue, DAB channel, easily obtained using the Fiji function: "ImageJ" -> "Image" -> "Colour Deconvolution" -> "FastRed FastBlue DAB" Then, the tool first segment the nuclei using the FastBlue channel and the DAB channel, and then computes statistics by subdividing the sample in three regions according to the FastRed channel: a dark-red ROI, a light-pink ROI and a white ROI. ANDTool is written in MATLAB (The MathWorks, Inc., Massachusetts, USA) and the source code and standalone versions are here available for download. USER MANUAL: see the specific PDF available in the Files section. REQUIREMENTS: MATLAB R2017b and Image Processing Toolbox 10.1 or later versions. ...

mexopencv is a collection of MEX functions that provide MATLAB bindings for OpenCV, the popular computer vision library. It enables MATLAB users to access nearly the full range of OpenCV’s C++ API directly from MATLAB, combining the ease of MATLAB scripting with the performance of OpenCV.

These functions implement a distance scaling method, proposed by Ye Zhu, Kai Ming Ting, and Maia Angelova, "A Distance Scaling Method to Improve Density-Based Clustering", in PAKDD2018 proceedings: https://doi.org/10.1007/978-3-319-93040-4_31.

This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package

...This packages contains the necessary codes to run on MATLAB. 2. The second package includes source and object files of DEMass-DBSCAN to be used with the WEKA system. 3. The third package DEMassBayes includes the source and object files of a Bayesian classifier using DEMass. DEMassBayes.7z has jar file to be used with WEKA and a readme file listing parameters used. The source files are included in DEMassBayes_Source.7z. 4. The four package is MassTER includes source and JAR file to be used with WEKA system..

...The CDTB contains several functions from the following categories. 1. graph generators; 2. clustering algorithms; 2. cluster number selection functions; 4. clustering evaluation functions. Furthermore, CDTB is designed in a parametric manner so that the user can add his own functions and extensions. The CDTB can be used in at least three ways. The user can employ the functions from the MATLAB command line; or he can write his own code, incorporating the CDTB functions; or he can use the Graphical User Interface (GUI) which automates the community detection and includes some data visualization options.

...The project used live video feeds from 10 underwater cameras as a testbed for investigating more generally applicable methods for capture, storage, analysis and querying of multiple video streams. We collated a public database from 3 years containing video summaries of the observed fish and associated descriptors. Expert web-based interfaces were developed for use by marine researchers, allowing unprecedented access to live and previously stored videos, or previously extracted information.

AERST is a C++ tool to simulate AER (Address-Event-Representation)-based systems

This project applies an interpretation of a k-NN algorithm to a library of GPS commuter data for speed prediction. The overall goal is to lay the foundation for a power management protocol for use in electric vehicles with hybrid energy storage.

Tool for visualizing artificial neural networks in Matlab using the Matlab Neural Network Toolbox (see wiki for details).

A graphical MatLab framework for estimating the parameters of, modeling and simulating static and dynamic linear and polynomial systems in the errors-in-variables context with the intent of comparing various estimation strategies.

Thank you for your interest in Speedy Composer. Speedy Composer is an automated application for composing melodies for Speedy Net members. We recently made changes to the source code of Speedy Net, and converted it into the Python language and Django framework. Since Speedy Composer was originally written in PHP, it is not adapted to work with Speedy Net in its current form. So unfortunately we were forced to temporarily close the app Speedy Composer. But don't worry, we kept backups of all...

The purpose of this program is to teach a computer to classify plants via their leaves. You just need to input the image of a leaf(acquired from scanner or camera), then the computer can tell you what kind of plant it is.

A scientific enterprise to try to learn basic patterns using directed acyclic graphs.

Matlab Classification Toolbox contains implementations of the following classifiers: Naive Bayes, Gaussian, Gaussian Mixture Model, Decision Tree and Neural Networks. This toolbox allows users to compare classifiers across various data sets.

NodeWeaver is a tool for generating SystemML Neuronal Networks from Neuronal Network descriptions (these technologies are nascent, so no links yet...). Intended use is to generate SystemML NNs for later execution using a SystemML simulator (e.g. BRAHMS).

This project consists in matlab scripts to create and train an Elman network. The task assigned to the network is to transform the orthographic form of a verb presented in the infinitive into its past participle and vice versa M.Carastro & R.Scanavino

neuro fuzzy net: 1. Object oriented Programming! 2. matlab project with back propagation, and hibrid learning. 3. Can use to MLP or ANFIS Sugeno modelling. 4. Integrated with Simulink (Sfunction M) by any questions mail me : tsepkovsky@yandex.ru

Matlab and Octave code to fit a mixture of Gaussians with covariance regularization to data using EM update rules.

EveAI processes the data assuming that it has already been read by a sensor. Theoretically this should give it reflex behavior. Now the end product should be a self conscious machine future plans are to include the field of robotics.