Search Results for author: Derek T. Anderson

Found 10 papers, 1 papers with code

Broad Area Search and Detection of Surface-to-Air Missile Sites Using Spatial Fusion of Component Object Detections from Deep Neural Networks

no code implementations23 Mar 2020 Alan B. Cannaday II, Curt H. Davis, Grant J. Scott, Blake Ruprecht, Derek T. Anderson

Here we demonstrate how Deep Neural Network (DNN) detections of multiple constitutive or component objects that are part of a larger, more complex, and encompassing feature can be spatially fused to improve the search, detection, and retrieval (ranking) of the larger complex feature.

Clustering Retrieval

Introducing Fuzzy Layers for Deep Learning

no code implementations21 Feb 2020 Stanton R. Price, Steven R. Price, Derek T. Anderson

Herein, we present a new deep learning strategy that incorporates fuzzy strategies into the deep learning architecture focused on the application of semantic segmentation using per-pixel classification.

Image Classification Road Segmentation

Extending the Morphological Hit-or-Miss Transform to Deep Neural Networks

no code implementations4 Dec 2019 Muhammad Aminul Islam, Bryce Murray, Andrew Buck, Derek T. Anderson, Grant Scott, Mihail Popescu, James Keller

While most deep learning architectures are built on convolution, alternative foundations like morphology are being explored for purposes like interpretability and its connection to the analysis and processing of geometric structures.

Fusion of heterogeneous bands and kernels in hyperspectral image processing

no code implementations22 May 2019 Muhammad Aminul Islam, Derek T. Anderson, John E. Ball, Nicolas H. Younan

Our approach is different in the respect that it is flexible and it follows a well-studied process of visual clustering in high-dimensional spaces.

Clustering Dimensionality Reduction

Fusion of an Ensemble of Augmented Image Detectors for Robust Object Detection

no code implementations17 Mar 2018 Pan Wei, John E. Ball, Derek T. Anderson

A significant challenge in object detection is accurate identification of an object's position in image space, whereas one algorithm with one set of parameters is usually not enough, and the fusion of multiple algorithms and/or parameters can lead to more robust results.

Image Augmentation Object +3

Measuring Conflict in a Multi-Source Environment as a Normal Measure

no code implementations12 Mar 2018 Pan Wei, John E. Ball, Derek T. Anderson, Archit Harsh, Christopher Archibald

The results demonstrate that the proposed measure can represent conflict in a meaningful way similar to what a human might expect and from it we can identify conflict within our sources.

Multi-Sensor Conflict Measurement and Information Fusion

no code implementations12 Mar 2018 Pan Wei, John E. Ball, Derek T. Anderson

In this work, conflict is defined in terms of how little the output from multiple sensors overlap.

Sensor Fusion

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