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Drupal Authentication modification for Pligg. Depends on still-unreleased project "Drupal Login Helper", so stay tuned!

Utility class to send emails from java using JavaMail

A web-based, D3&Websocket powered maze visualizer for Hipster!

Sensor Observation Service Virtual Data Integration

Plantilla para a realización de technical reports

Wrapper for ROS of Depth Sense SDK ( cameras Creative Senz3d o DS325). Based on the wrapper developed by Walter Lucetti aka Myzhar https://github.com/Myzhar/ros_depthsense_camera

Windows 64bit executables Two-view line matching algorithm based on context and appearance in low-textured images. Pattern Recognition Volume 48, Issue 7, July 2015, Pages 2164–2184 http://www.sciencedirect.com/science/article/pii/S0031320314004889

Experimental results related to the paper ELM-based Spectral-Spatial Classification of Hyperspectral Images using Extended Morphological Profiles and Composite Feature Mappings published in the International Journal of Remote Sensing.

Experimental results related to the paper "Spectral-Spatial Classification of Hyperspectral Images Based on Convolutional Neural Networks"

Clase de LaTeX para a elaboración de tesis no formato CITIUS.

This project contains the material used to carry out the study of the following paper: "On the use of feature selection to improve oil spill detection in SAR images"

Texture features extracted from histological images of fish ovary. Total 4 sets; 3.868 instances. 25 (rep. 41) inputs, 2 (resp. 3) classes to detect the cell nucleous (resp. to classify maturity cell states).

The inputs are bands of infrared hyperspectral imaging data of potatoes. 126 instances, 256 inputs, 2 classes (presence/absence of common scab in potatoes).

The inputs are shape and texture features extracted from microscopical images of pollen grains in the air. 291 instances, 23 inputs, 3 classes (species of plants Parietaria Judaica, urtica urens and urtica membranacea).

The inputs are texture features extracted from images of honeybee pollen loads captured by a stereo microscope connected to a digital camera. 2.600 instances, 70 inputs, 5 classes (species of plants cytisus, castanea, quercus, rubus and paphanus).

Sync Projects maintained only on Github into Gitlab, for operational reasons.