Abstract: The Extended Functions of Multiple Instances (eFUMI) algorithm is a generalization of Multiple Instance Learning (MIL). In eFUMI, only bag level (i.e. set level) labels are needed to estimate target signatures from mixed data. The training bags in eFUMI… Read More
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Task Driven Extended Functions of Multiple Instances
Abstract: Dictionary learning techniques have proven to be a powerful method in the pattern recognition literature. Recently supervised dictionary learning has been used to achieve very good results on a number of different data types and applications. However, these supervised… Read More
Sand ripple characterization using an extended synthetic aperture sonar model and parallel sampling method
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Abstract: The aim of this work is to characterize the seafloor by estimating invariant sand ripple parameters from synthetic aperture sonar (SAS) imagery. Using a hierarchical Bayesian framework and a known sensing geometry, a method for estimating sand ripple frequency,… Read More
Bayesian fuzzy clustering
Abstract: We present a Bayesian probabilistic model and inference algorithm for fuzzy clustering that provides expanded capabilities over the traditional Fuzzy C-Means approach. Additionally, we extend the Bayesian Fuzzy Clustering model to handle a variable number of clusters and present… Read More
Functions of Multiple Instances for Learning Target Signatures
Abstract: The functions of multiple instances (FUMI) approach for learning target and nontarget signatures is introduced. FUMI is a generalization of the multiple-instance learning (MIL) approach for supervised learning. FUMI differs significantly from standard MIL and supervised learning approaches because… Read More
Random projections fuzzy c-means (RPFCM) for big data clustering
Abstract: Many contemporary biomedical applications such as physiological monitoring, imaging, and sequencing produce large amounts of data that require new data processing and visualization algorithms. Algorithms such as principal component analysis (PCA), singular value decomposition and random projections (RP) have… Read More
Estimating Target Signatures with Diverse Density
Abstract: Hyperspectral target detection algorithms rely on knowing the desired target signature in advance. However, obtaining an effective target signature can be difficult; signatures obtained from laboratory measurements or hand-spectrometers in the field may not transfer to airborne imagery effectively.… Read More
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… Read More
Anomaly detection of subsurface objects using handheld ground-penetrating radar
Abstract: This paper develops an anomaly detection algorithm for subsurface object detection using the handheld ground penetrating radar. The algorithm is based on the Mahalanobis distance measure with adaptive update of the background statistics. It processes the data sequentially for… Read More
Functions of multiple instances for sub-pixel target characterization in hyperspectral imagery
Abstract: In this paper, the Multi-target Extended Function of Multiple Instances (Multi-target eFUMI) method is developed and described. The method is capable of learning multiple target spectral signatures from weakly- and inaccurately-labeled hyperspectral imagery. Multi-target eFUMI is a generalization of… Read More