Congratulations to Gatorsense alumna, Xiaoxiao Du! Her paper, titled “Multiple Instance Choquet Integral with Binary Fuzzy Measures for Remote Sensing Classifier Fusion with Imprecise Labels”, was recently accepted for publication with The 2019 IEEE Symposium Series on Computational Intelligence (IEEE… Read More
Tag: choquet integral
Multiple Instance Choquet Integral with Binary Fuzzy Measures for Remote Sensing Classifier Fusion with Imprecise Labels
Abstract: Classifier fusion methods integrate complementary information from multiple classifiers or detectors and can aid remote sensing applications such as target detection and hyperspectral image analysis. The Choquet integral (CI), parameterized by fuzzy measures (FMs), has been widely used in… Read More
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… Read More
Measures of the Shapley index for learning lower complexity fuzzy integrals
Abstract: The fuzzy integral (FI) is used frequently as a parametric nonlinear aggregation operator for data or information fusion. To date, numerous data-driven algorithms have been put forth to learn the FI for tasks like signal and image processing, multi-criteria… Read More
Aggregation of Choquet integrals in GPR and EMI for handheld platform-based explosive hazard detection
Abstract: Substantial interest resides in identifying sensors, algorithms and fusion theories to detect buried explosive hazards. This is a significant research effort because it impacts the safety and lives of civilians and soldiers alike. Herein, we explore the fusion of… Read More
Binary Fuzzy Measures and Choquet Integration for Multi-Source Fusion
Abstract: Countless challenges in engineering require the intelligent combining (aka fusion) of data or information from multiple sources. The Choquet integral (ChI), a parametric aggregation function, is a well-known tool for multisource fusion, where source refers to sensors, humans and/or… Read More
Genetic Programming Based Choquet Integral for Multi-Source Fusion
Abstract: While the Choquet integral (ChI) is a powerful parametric nonlinear aggregation function, it has limited scope and is not a universal function generator. Herein, we focus on a class of problems that are outside the scope of a single… Read More
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… Read More
Vegetation mapping for landmine detection using long-wave hyperspectral imagery
Abstract: We develop a vegetation mapping method using long-wave hyperspectral imagery and apply it to landmine detection. The novel aspect of the method is that it makes use of emissivity skewness. The main purpose of vegetation detection for mine detection… Read More
Sensor fusion for airborne landmine detection
Abstract: Sensor fusion has become a vital research area for mine detection because of the countermine community’s conclusion that no single sensor is capable of detecting mines at the necessary detection and false alarm rates over a wide variety of… Read More