An acoustic event classifier uses particle swarm optimization (PSO) to perform a flexible time correlation of a sensed acoustic signature to reference acoustic signatures in a multi-dimensional parameter space. The classifier may fuse the acoustic signatures from multiple acoustic sensors to form the sensed acoustic signature. The approach is generally applicable to classify all types of acoustic events but is particularly well-suited to classify “explosive” events such as gun shots, mortar blasts, improvised explosive device blasts etc.that produce an acoustic signature having a shock wave component that is periodic and non-linear.
James F. Alves - Calabasas CA Jerry A. Burman - Westlake Village CA
Assignee:
Hughes Aircraft Company - Los Angeles CA
International Classification:
G06K 936
US Classification:
382 56
Abstract:
Data decompression of an image is implemented by reconstructing blocks of pixels from a table that stores orthogonal icons and related attributes representing a data compressed image. Each block of pixels is processed independently of all other blocks. Orthogonal processing is employed to reconstruct orthogonal features that relate to manufactured elements in an image. An optimum set of orthogonal icons and an optimum set of attributes for each icon are employed to further improve data decompression and fidelity. The optimal set of orthogonal icons includes a flat icon, an edge icon, a ribbon icon, a corner icon and a spot icon. The optimal set of attributes includes average intensities, intensity transition position and separation, and angle of the principal axis.
James F. Alves - Calabasas CA Jerry A. Burman - Westlake Village CA
Assignee:
Hughes Aircraft Company - Los Angeles CA
International Classification:
G06K 900
US Classification:
382 56
Abstract:
Image data compression is implemented by partitioning an image into relatively small blocks of pixels, matching each block to an orthogonal icon, and extracting attributes associated with the icon. A table of these orthogonal icons and attributes represents a data compressed image. Each block is processed separately from all other blocks. Orthogonal processing is used to preserve orthogonal features while attenuating non-orthogonal features. An optimum set of orthogonal icons and an optimum set of attributes for each icon further improves data compression and fidelity. The optimal set of orthogonal icons includes a flat icon, an edge icon, a ribbon icon, a corner icon, and a spot icon. An optimal set of attributes includes average intensities, intensity transition position and separation, and angle of the principal axes.
Pattern Recognition Apparatus Utilizing Area Linking And Region Growth Techniques
James F. Alves - Calabasas CA Jerry A. Burman - Westlake Village CA Victoria Gor - Canoga Park CA Michele K. Daniels - Northridge CA Walter W. Tackett - Canoga Park CA Craig C. Reinhart - Moorpark CA Bruce A. Berger - Simi Valley CA Brian J. Birdsall - Canoga Park CA
Assignee:
Hughes Aircraft Company - Los Angeles CA
International Classification:
G06K 948
US Classification:
382 22
Abstract:
Image data is processed by a low level feature detection processor that extracts low level features from an image. This is accomplished by converting a matrix of image data into a matrix of orthogonal icons that symbolically represent the image scene using a predetermined set of attributes. The orthogonal icons serve as the basis of processing by means of a high level graph matching processor which employs symbolic scene segmentation, description, and recognition processing that is performed subsequent to the low level feature detection. This processing generates attribute graphs representative of target objects present in the image scene. High level graph matching compares predetermined attributed reference graphs to the sensed graphs to produce a best common subgraph between the two based on the degree of similarity between the two graphs. The high level graph matching generates a recognition decision based on the value of the degree of similarity and a predetermined threshold. The output of the high level graph matching provides data from which a target aimpoint is determined, and this aimpoint is coupled as an input to a missile guidance system that tracks identified targets.
Apparatus For Providing A Composite Digital Representation Of A Scene Within A Field-Of-Regard
Jerry A. Burman - Westlake Village CA Walter A. Tackett - Granada Hills CA Gina Berry - Northridge CA
Assignee:
Hughes Aircraft Company - Los Angeles CA
International Classification:
G06F 1562
US Classification:
395135
Abstract:
A high resolution imaging system having a wide field-of-regard. The wide field image generation system (10) of the present invention is operative to provide a composite digital representation of a scene within a field-of-regard. The invention (10) includes a sensor arrangement (12, 14, and 16) for generating first and second frames of image data. A scene correlator (18) registers the first and second frames of image data within the field-of-regard. A temporal filter (22) averages image data in the first frame with image data at a respective corresponding location in the second frame to provide a third frame of image data. When displayed, the third frame of image data provides a wide field-of-regard, high resolution image with minimal undesirable seams therein.
Resumes
Senior Research Scientist At Teledyne Scientific Company
Deloitte
Data Scientist, Deloitte Vigilant, Cyber Security
Intelligent Recognition Systems Mar 2012 - Jun 2014
Senior Research Scientist
Teledyne Scientific & Imaging Feb 2005 - Mar 2012
Senior Research Scientist
Education:
Alexander Hamilton High School
University of California, Los Angeles
Masters, Mathematics
University of California, Los Angeles
Bachelors, Mathematics, Physics
University of California, Los Angeles
Masters, Master of Science In Electrical Engineering, Engineering
Stanford University
Doctorates, Doctor of Philosophy, Engineering
Skills:
Machine Learning Predictive Analytics Artificial Intelligence Neural Networks Data Science Big Data Pattern Recognition Signal Processing Image Processing Information Extraction Automated Reasoning Algorithm Development Bio Inspired Technologies Matlab Cyber Security Insider Threat Detection Algorithms Data Analysis Data Mining Simulations R Statistics Latex
Deloitte Jun 2014 - Aug 2016
Research Scientist: Data Analtics and Artificial Intelligence
Intelligent Analytic Systems Jun 2014 - Aug 2016
Chief Technology Officer Data Analytics
Intelligent Recognition Systems Mar 2012 - Jun 2014
Senior Research Scientist and Chief Technology Officer
Teledyne Scientific & Imaging Mar 2005 - Mar 2012
Senior Research Scientist and Technical Program Manager
Education:
University of California, Los Angeles
Master of Science, Masters, Electronics Engineering
University of California, Los Angeles
Masters, Mathematics
University of California, Los Angeles
Bachelors, Mathematics, Physics
Stanford University
Doctorates, Doctor of Philosophy, Engineering
Skills:
Optics Physics Engineering Management Linux Algorithms Systems Engineering C Matlab Data Analysis Sensors Electronics System Design Image Processing Avi Carmi Engineering Uav Signal Processing Artificial Intelligence Programming Embedded Systems Program Management Testing Proposal Writing Labview C++ Simulation Computer Vision Dsp Software Engineering Robotics Simulations Semiconductors Optimization Research Software Development Digital Signal Processors Machine Learning Digital Image Processing Statistics R&D Analysis Automation
Teledyne Technologies Incorporated
Senior Research Scientist
Education:
Stanford University
Doctorates, Doctor of Philosophy, Engineering
University of California, Los Angeles
Masters, Master of Science In Electrical Engineering, Engineering
University of California, Los Angeles
Masters, Master of Arts, Bachelors, Bachelor of Arts, Mathematics, Physics
Jerry Burman 1967 graduate of Alexander Hamilton High School in Los angeles, CA is on Memory Lane. Get caught up with Jerry and other high school alumni from ...
Jerry Burman 1984 graduate of Plainview-Old Bethpage High School in Plainview, NY is on Memory Lane. Get caught up with Jerry and other high school alumni from ...