0000000000528407

AUTHOR

José Antonio Padrón

showing 2 related works from this author

Randomized Rx For Target Detection

2018

This work tackles the target detection problem through the well-known global RX method. The RX method models the clutter as a multivariate Gaussian distribution, and has been extended to nonlinear distributions using kernel methods. While the kernel RX can cope with complex clutters, it requires a considerable amount of computational resources as the number of clutter pixels gets larger. Here we propose random Fourier features to approximate the Gaussian kernel in kernel RX and consequently our development keep the accuracy of the nonlinearity while reducing the computational cost which is now controlled by an hyperparameter. Results over both synthetic and real-world image target detection…

FOS: Computer and information sciencesHyperparameter020301 aerospace & aeronauticsComputer Science - Machine LearningComputer scienceComputer Vision and Pattern Recognition (cs.CV)0211 other engineering and technologiesComputer Science - Computer Vision and Pattern RecognitionMultivariate normal distribution02 engineering and technologyObject detectionMachine Learning (cs.LG)symbols.namesakeKernel (linear algebra)Kernel method0203 mechanical engineeringKernel (statistics)Gaussian functionsymbolsClutterAnomaly detectionAlgorithm021101 geological & geomatics engineering
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HyperLabelMe : A Web Platform for Benchmarking Remote-Sensing Image Classifiers

2017

HyperLabelMe is a web platform that allows the automatic benchmarking of remote-sensing image classifiers. To demonstrate this platform's attributes, we collected and harmonized a large data set of labeled multispectral and hyperspectral images with different numbers of classes, dimensionality, noise sources, and levels. The registered user can download training data pairs (spectra and land cover/use labels) and submit the predictions for unseen testing spectra. The system then evaluates the accuracy and robustness of the classifier, and it reports different scores as well as a ranked list of the best methods and users. The system is modular, scalable, and ever-growing in data sets and clas…

General Computer ScienceContextual image classificationComputer scienceMultispectral imageRegistered user020206 networking & telecommunications02 engineering and technologyBenchmarkingcomputer.software_genreData setStatistical classificationComputingMethodologies_PATTERNRECOGNITIONRobustness (computer science)ITC-ISI-JOURNAL-ARTICLE0202 electrical engineering electronic engineering information engineeringGeneral Earth and Planetary Sciences020201 artificial intelligence & image processingData miningElectrical and Electronic EngineeringInstrumentationcomputerClassifier (UML)IEEE Geoscience and Remote Sensing Magazine
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