Multiple Instance Choquet Integral For MultiResolution Sensor Fusion
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 a big yellow umbrella outside. After you land, you need directions to the hotel from the airport. Suppose you are driving a rental car, you …
Read more “Multiple Instance Choquet Integral For MultiResolution Sensor Fusion”
Technical Report: Scene Label Ground Truth Map for MUUFL Gulfport Data Set
Abstract This report presents the documentation of the ground truth map for MUUFL Gulfport data set campus 1 scene, provided by manually labeling the pixels in the scene into trees, mostly-grass ground surface, mixed ground surface, dirt and sand, road, water, buildings, shadow of buildings, sidewalk, yellow curb, cloth panels (targets), and unlabeled points. This …
Read more “Technical Report: Scene Label Ground Truth Map for MUUFL Gulfport Data Set”
Environmentally-Adaptive Target Recognition for SAS Imagery
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 discriminative in sand ripple, for example. Environmentally-adaptive target detection and classification systems that take into account environmental context, therefore, have the potential for improved results. …
Read more “Environmentally-Adaptive Target Recognition for SAS Imagery”
Multiple-instance Learning-based Sonar Image Classification
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 and texture feature distributions. These superpixels are defined as the “instances” and the sonar images are defined as the “bags” within the MILES classification framework. …
Read more “Multiple-instance Learning-based Sonar Image Classification”
Multiple Instance Choquet Integral for Classifier Fusion
Abstract The Multiple Instance Choquet integral (MICI) for classifier fusion and an evolutionary algorithm for parameter estimation is presented. The Choquet integral has a long history of providing an effective framework for non-linear fusion. Previous methods to learn an appropriate measure for the Choquet integral assumed accurate and precise training labels (with low levels of …
Read more “Multiple Instance Choquet Integral for Classifier Fusion”
Possibilistic context identification for SAS imagery
Abstract This paper proposes a possibilistic context identification approach for synthetic aperture sonar (SAS) imagery. SAS seabed imagery can display a variety of textures that can be used to identify seabed types such as sea grass, sand ripple and hard-packed sand, etc. Target objects in SAS imagery often have varying characteristics and features due to …
Read more “Possibilistic context identification for SAS imagery”