Abstract: The use of handheld ground penetrating radar (GPR) for subsurface object detection often faces challenges coming from the human operator effect, antenna height variation and uneven data sample spacing. This paper investigates the artifact of uneven sample spacing on… Read More
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A novel multi-perspective imaging platform (M-PIP) for phenotyping soybean root crowns in the field increases throughput and separation ability of genotype root properties
Abstract: Background: Root crown phenotyping has linked root properties to shoot mass, nutrient uptake, and yield in the field, which increases the understanding of soil resource acquisition and presents opportunities for breeding. The original methods using manual measurements have been… Read More
Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label Uncertainty
Abstract: In remote sensing, each sensor can provide complementary or reinforcing information. It is valuable to fuse outputs from multiple sensors to boost overall performance. Previous supervised fusion methods often require accurate labels for each pixel in the training data.… Read More
Quantitative Evaluation Metrics for Superpixel Segmentation
Abstract: Superpixel segmentation methods have been found to be increasingly valuable in image processing and analysis. Superpixel segmentation approaches have been used as a preprocessing step for a wide variety of image analysis tasks such as full scene segmentation, automated… Read More
Comparison of Prescreening Algorithms for Target Detection in Synthetic Aperture Sonar Imagery
Abstract: Automated anomaly and target detection are commonly used as a prescreening step within a larger target detection and target classification framework to find regions of interest for further analysis. A number of anomaly and target detection algorithms have been… Read More
Possibilistic fuzzy local information C-means with automated feature selection for seafloor segmentation
Abstract: The Possibilistic Fuzzy Local Information C-Means (PFLICM) method is presented as a technique to segment side-look synthetic aperture sonar (SAS) imagery into distinct regions of the sea-floor. In this work, we investigate and present the results of an automated… Read More
Multiple Instance Choquet Integral Classifier Fusion and Regression for Remote Sensing Applications
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 labels. However, accurate labels may be difficult to obtain in… Read More
Target Concept Learning From Ambiguously Labeled Data
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 detection from remotely sensed hyperspectral imagery, targets are usually sub-pixel… 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
Multiple Instance Hybrid Estimator for Hyperspectral Target Characterization and Sub-pixel Target Detection
Abstract: The Multiple Instance Hybrid Estimator for discriminative target characterization from imprecisely labeled hyperspectral data is presented. In many hyperspectral target detection problems, acquiring accurately labeled training data is difficult. Furthermore, each pixel containing target is likely to be a… Read More