Data Exploitation
Data Exploitation Group - Mission
Michigan Aerospace Corporation’s Data Exploitation Group applies data mining, pattern
recognition, machine learning and image processing technologies to develop products for the defense and civil space
communities, as well as the private sector. The staff of this group has over three decades of experience in delivering
pattern recognition solutions to the United States government and private industries, including chemical companies,
pharmaceutical, biotechnology, and automotive. We have the combination of technologies and application experience in data
exploitation software to understand our customers' problems and deliver quality software solutions.
Novelty and Anomaly Detection
MAC's Data Exploitation Group provides customizable software and services for anomaly
and novelty detection. Products for discovering novel events and detecting anomalous behavior are quickly becoming
indispensable for the proper operation and maintenance of the complex systems employed by modern industry, medical
providers and the military. Factories, health monitors, aircraft and other vehicles regularly produce hundreds or
thousands of channels of telemetry in real time, which must be monitored for possible indications of failure. These
data resources present an enormous opportunity for software tools that can detect events of interest. These tools can
be used to discover useful new insights into operations, diagnose faults post mortem to determine the cause, and predict
failures before they cause costly damage or injury.
Our group has developed powerful pattern recognition technology, based on Ensembles of Decision Trees (EDTs), which drives
our tools for novelty and anomaly detection. EDT-based technology has many advantages over existing techniques, including
the scalability to handle very high dimensional data, automatic drill-down facilities to explain why an event is
categorized as novel or anomalous, and extremely rapid evaluation. The approach is also amenable to deployment on FPGA
devices, Graphical Processing Units, parallel processors and other accelerated platforms.

Pattern Recognition / Machine Learning / Data Mining
MAC's staff have intimate knowledge and practical experience using the approaches seen in the following table:
Neural Networks |
Decision Trees and Ensembles |
Support Vector Machines |
K Nearest Neighbors |
Clustering Techniques |
Bayesian Learning |
Evolutionary Algorithms |
Hidden Markov Models |
Self Organizing Maps (SOMs) |
Computer Vision and Image Processing
The Data Exploitation Group’s scientists have accumulated a wealth of expertise in arenas related to computer vision including image processing, visualization, machine learning, optimization, and pattern recognition.
Our scientists have expertise in many facets of image analysis including:
Using these low-level paradigms our researchers have developed and implemented algorithms in previous projects crucial for computer vision tasks such as:
Preprocessing, Calibration, Normalization, and Enhancement
Feature Extraction
Measuring of Image Attributes (Texture, Shape, Color, etc.)
Registration and Mosaicking
Segmentation and Thresholding
Object Detection, Classification and Recognition
Target Tracking
These algorithms have been developed for a broad array of imaging modalities from many arenas including:
-
3D laser range and reflectance
-
Multispectral imagery (Thematic Mapper [TM], LandSAT, and Spot)
-
Synthetic Aperture Radar (SAR) imagery
-
Stereo pair imagery
|
|