Articles Tagged uncertain/imprecise labels Subscribe to RSS Feed

Multiple Instance Choquet Integral Classifier Fusion and Regression for Remote Sensing Applications

Published: Mar 13th, 2018

Abstract: In classifier (or regression) fusion the aim is to combine the outputs of several algorithms to boost overall performance. Standard supervised fusion algorithms often require accurate and precise training […]

Target Concept Learning From Ambiguously Labeled Data

Published: Dec 18th, 2017

Abstract: The multiple instance learning problem addresses the case where training data comes with label ambiguity, i.e., the learner has access only to inaccurately labeled data. For example, in target […]

Multiple Instance Choquet Integral For MultiResolution Sensor Fusion

Published: Dec 18th, 2017

Abstract: Imagine you are traveling to Columbia,MO for the first time. On your flight to Columbia, the woman sitting next to you recommended a bakery by a large park with […]

Multiple Instance Dictionary Learning for Beat-to-Beat Heart Rate Monitoring from Ballistocardiograms

Published: Jun 15th, 2017

Abstract: A multiple instance dictionary learning approach, Dictionary Learning using Functions of Multiple Instances (DLFUMI), is used to perform beat-to-beat heart rate estimation and to characterize heartbeat signatures from ballistocardiogram […]

Multiple-instance learning-based sonar image classification

Published: Mar 17th, 2017

Abstract: An approach to image labeling by seabed context based on multiple-instance learning via embedded instance selection (MILES) is presented. Sonar images are first segmented into superpixels with associated intensity […]

Environmentally-Adaptive Target Recognition for SAS Imagery

Published: Mar 17th, 2017

Abstract: Characteristics of underwater targets displayed in synthetic aperture sonar (SAS) imagery vary depending on their environmental context. Discriminative features in sea grass may differ from the features that are […]

Hyperspectral Unmixing with Endmember Variability using Semi-supervised Partial Membership Latent Dirichlet Allocation

Published: Mar 17th, 2017

Abstract: A semi-supervised Partial Membership Latent Dirichlet Allocation approach is developed for hyperspectral unmixing and endmember estimation while accounting for spectral variability and spatial information. Partial Membership Latent Dirichlet Allocation […]

Map-guided Hyperspectral Image Superpixel Segmentation Using Proportion Maps

Published: Jan 10th, 2017

Abstract: A map-guided superpixel segmentation method for hyperspectral imagery is developed and introduced. The proposed approach develops a hyperspectral-appropriate version of the SLIC superpixel segmentation algorithm, leverages map information to […]

Multiple Instance Hybrid Estimator for Learning Target Signatures

Published: Jan 10th, 2017

Abstract: Signature-based detectors for hyperspectral target detection rely on knowing the specific target signature in advance. However, target signature are often difficult or impossible to obtain. Furthermore, common methods for […]

Map-guided Hyperspectral Image Superpixel Segmentation Using Semi-supervised Partial Membership Latent Dirichlet Allocation

Published: Dec 20th, 2016

Abstract: Many superpixel segmentation algorithms which are suitable for the regular color images like images with three channels: red, green and blue (RGB images) have been developed in the literature. […]