Dr. Tien Pham Profile

Dr. Tien Pham

AI Assurance Solutions Lead

SPIE Involvement:

Conference Program Committee | Symposium Chair | Track Chair | Editor | Author

Area of Expertise:

Signal Processing , Sensor Networks , Acoustics , Data Fusion , Coalition Interoperability , Multi-modal Sensing

Websites:

Company Website

Profile Summary

Dr. Pham is a Senior Scientific Technical Manager (SSTM) and an ARL Fellow at the U.S. Army Combat Capabilities Development Command (DEVCOM) Army Research Laboratory (ARL). He currently serves as the Chief Scientist for the Computational & Information Sciences Directorate (CISD). He helps oversee basic and applied research associated with the ARL Foundational Research Competencies in Military Information Sciences (MIS) and Network, Cyber and Computational Sciences (NC&CS) and the cross-cutting research efforts in Artificial Intelligence and Machine Learning (AI/ML).

Publications (35)

Proceedings Article | 6 June 2022 Poster + Presentation + Paper

Poster + Presentation + Paper

Advanced machine learning methods for autonomous classification of ground vehicles with acoustic data

Xingchi Liu, Qing Li, Jiaming Liang, Jinzheng Zhao, Peipei Wu, Chenyi Lyu, Shidrokh Goudarzi, Jemin George, Tien Pham, Wenwu Wang, Lyudmila Mihaylova, Simon Godsill

Proceedings Volume 12113, 121131P (2022) https://doi.org/10.1117/12.2618105

KEYWORDS: Acoustics, Sensors, Machine learning, Feature extraction, Data fusion, Analytical research, Time-frequency analysis, Signal to noise ratio

Read Abstract +

Proceedings Article | 12 April 2021 Presentation

Presentation

Welcome and Introduction to SPIE Conference 11746

Tien Pham, Latasha Solomon, Myron Hohil

Proceedings Volume 11746, 1174604 (2021) https://doi.org/10.1117/12.2597578

Read Abstract +

Proceedings Article | 12 April 2021 Presentation

Presentation

US Army international AI initiatives: xTech Global and AI FIVES

Jonathon Brame, Kelly Risko, Nathan Anderson, Tien Pham

Proceedings Volume 11746, 117460G (2021) https://doi.org/10.1117/12.2593531

Read Abstract +

Proceedings Article | 27 April 2020 Presentation

Presentation

11413 on AI & ML for MDO Applications II: Introduction (Conference Presentation)

Tien Pham

Proceedings Volume 11413, 1141303 (2020) https://doi.org/10.1117/12.2572445

Read Abstract +

Proceedings Article | 23 April 2020 Presentation

Presentation

Coalition situational understanding for multi-domain operations (Conference Presentation)

Alun Preece, Federico Cerutti, Dave Braines, Supriyo Chakraborty, Mani Srivastava, Tien Pham

Proceedings Volume 11413, 1141307 (2020) https://doi.org/10.1117/12.2558571

KEYWORDS: Machine learning

Read Abstract +

Proceedings Article | 10 May 2019 Paper

Paper

Design and implementation of the U.S. Army Artificial Intelligence Innovation Institute

Greg Cirincione, Tien Pham, Andrew Ladas, Brian Stanton, Gregory Fischer

Proceedings Volume 11006, 110060B (2019) https://doi.org/10.1117/12.2524026

Read Abstract +

Proceedings Article | 14 May 2018 Open Access

Open Access

Presentation

Army Research Laboratory essential research area: AI and ML (Conference Presentation)

Brian Henz, Tien Pham

Proceedings Volume 10639, 106391R (2018) https://doi.org/10.1117/12.2309876

KEYWORDS: Analytical research, Artificial intelligence

Read Abstract +

Proceedings Article | 14 May 2018 Presentation

Presentation

Intelligent resource selection for sensor-task assignment: the story so far (Conference Presentation)

Geeth de Mel, Tien Pham

Proceedings Volume 10643, 106430O (2018) https://doi.org/10.1117/12.2305140

KEYWORDS: Sensors, Intelligent sensors, Surveillance, Network architectures

Read Abstract +

Proceedings Article | 4 May 2018 Presentation + Paper

Presentation + Paper

Generation and management of training data for AI-based algorithms targeted at coalition operations

Dinesh Verma, Greg Cirincione, Tien Pham, Bong Jun Ko

Proceedings Volume 10635, 106350U (2018) https://doi.org/10.1117/12.2305244

KEYWORDS: Sensors, Intelligence systems, Machine learning, Data storage, Data acquisition, Artificial intelligence

Read Abstract +

Proceedings Article | 7 June 2017 Presentation

Presentation

Instinctive analytics for coalition operations (Conference Presentation)

Geeth de Mel, Thomas La Porta, Tien Pham, Gavin Pearson

Proceedings Volume 10190, 1019008 (2017) https://doi.org/10.1117/12.2266579

KEYWORDS: Lanthanum, Defense and security, Intelligence systems, Current controlled current source, Analytics, Data modeling, Data processing, Data fusion, Visual process modeling, Directed self assembly

Read Abstract +

Proceedings Article | 12 May 2016 Paper

Paper

Sensor assignment to mission in AI-TECD

Robert Ganger, Geeth de Mel, Tien Pham, Ronald Rudnicki, Yonatan Schreiber

Proceedings Volume 9831, 98310E (2016) https://doi.org/10.1117/12.2229406

KEYWORDS: Sensors, Fourier transforms, Standards development, Data modeling, Environmental sensing, Infrared sensors, Clouds, Ecosystems, Analytical research, Software development

Read Abstract +

Proceedings Article | 12 May 2016 Paper

Paper

ARL PED efforts at enterprise challenge 2016

Susan Toth, William Hughes, Tien Pham, Jeffrey Houser

Proceedings Volume 9831, 983107 (2016) https://doi.org/10.1117/12.2229481

KEYWORDS: Sensors, 3D modeling, Intelligence systems, Video, Environmental sensing, Unattended ground sensors, Data storage, Visualization, Standards development, Digital video recorders

Read Abstract +

Proceedings Article | 20 May 2015 Paper

Paper

PED fusion via enterprise ontology

James Schoening, Danielle Duff, Dorothy Hines, Keith Riser, Tien Pham, Gary Stolovy, Jeff Houser, Ronald Rudnicki, Robert Ganger, Alex James, Eric Nagler

Proceedings Volume 9464, 94640D (2015) https://doi.org/10.1117/12.2182064

KEYWORDS: Sensors, Biometrics, Intelligence systems, Data storage, Intelligent sensors, Unmanned aerial vehicles, Data fusion, Neodymium, Unattended ground sensors, Data processing

Read Abstract +

In the Army Intelligence domain, Processing, Exploitation, and Dissemination (PED) is the process that is used to convert and collect information into actionable intelligence and then distribute this intelligence appropriately to those who make decisions and execute the tasks and missions that this intelligence process supports. In today’s Intelligence domain, information is gathered from an abundance of sources and these sensors create an exponential amount of data output. PED is a time sensitive process, which is also constrained by manpower and the extremely limited tactical bandwidth. Currently, PED is primarily a higher echelon activity, but as information gathering increases at the platforms it makes sense to automate PED tasks and execute these tasks closer to the sensor sources. Providing an architecture that will allow for processing sensor data more intelligently at various locations within the Intel network to include: on-board a UAV or vehicle, COIST, and higher echelons can help to alleviate these constraints by positioning the sensor fusion as close as possible to minimize bandwidth utilization. However, this architecture will implicitly need a way to share data to enable fusion. While any given mission may require fusion of just a few sensor data sources, which can be accomplished with point-to-point integration, this approach does not scale and is not maintainable, since the range of all missions will require a combination of any number of data sources and this approach will most likely require extra development to handle new sources. Therefore, there needs to be a way to share and reuse date that is extensible, maintainable, and not tied to any one mission type. This approach will reduce duplication, provide common patterns for accessing information and support future growth. This paper describes how a common ontology can be used to transform intelligence data from any number of disparate sources to a higher level of integration where one uses the logical understanding of the domain to share knowledge between sources. This paper will discuss sensor ontology efforts to date, introduce the Common Core Ontologies which provide the common upper and mid-level semantics which are inherited by domain level ontologies and describe future experimentation. The paper will discuss the role of the Common Core Ontologies development and governance practices in producing a logically consistent data set, which can be accessed through a single API. By utilizing this approach, sensor outputs can be fused using inferencing, entity and event resolution, and other 3rd party analytic apps. Finally, the paper will also describe how ontologies are leveraged to enable tasking, analytics, rules based reasoning, and distributed processing which are functional components currently being utilized or developed to support the PED process.

Proceedings Article | 7 June 2013 Paper

Paper

Controlled English to facilitate human/machine analytical processing

Dave Braines, David Mott, Simon Laws, Geeth de Mel, Tien Pham

Proceedings Volume 8758, 875808 (2013) https://doi.org/10.1117/12.2015907

KEYWORDS: Data modeling, Telecommunications, Image processing, Analytical research, Sensors, Data processing, Logic, Information fusion, Java, Human-machine interfaces

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Proceedings Article | 28 May 2013 Paper

Paper

Reasoning with uncertain information and trust

Murat Sensoy, Geeth de Mel, Achille Fokoue, Timothy Norman, Jeff Pan, Yuqing Tang, Nir Oren, Katia Sycara, Lance Kaplan, Tien Pham

Proceedings Volume 8758, 87580C (2013) https://doi.org/10.1117/12.2015667

KEYWORDS: Lead, Logic, Analytical research, Bismuth, Roads, Fuzzy logic, Defense and security, Acoustics, Systems modeling, Sensors

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Proceedings Article | 22 May 2013 Paper

Paper

Coalition Warfare Program (CWP): secure policy controlled information query and dissemination over a Bices network

Andrew Toth, Tien Pham, Todd Karr, Graham Bent, Dominic Harries, Alan Knox

Proceedings Volume 8742, 87420F (2013) https://doi.org/10.1117/12.2018530

KEYWORDS: Databases, Computer security, Network security, Information security, Data modeling, Warfare, Analytical research, Defense and security, Software development, Standards development

Read Abstract +

In 2006, the US Army Research Laboratory (ARL) and the UK Ministry of Defence (MoD) established a collaborative research alliance with academia and industry, called the International Technology Alliance (ITA) to address fundamental issues concerning Network and Information Sciences. Under the ITA research program, a US-UK transition project on "ITA Policy Controlled Information Query and Dissemination" was funded in 2011 by OSD's Coalition Warfare Program (CWP). The goal of this CWP project is to develop an extensible capability of performing distributed federated query and information dissemination across a coalition network of distributed disparate data/information sources with access controlled policies. The CWP project is lead by US Army Research Laboratory (ARL) and UK Defence Science Technology Laboratory (Dstl) with software development by IBM UK and IBM US. The CWP project exploits two key technology components developed within the ITA, namely the Gaian Database and integrated Access Policy Decision and Enforcement mechanisms. The Gaian Database (GaianDB) is a Dynamic Distributed Federated Database (DDFD) that addresses a need to share information among coalition members by providing a means for policy-controlled access to data across a network of heterogeneous data sources. GaianDB implements a SQL-compliant Store-Locally-Query-Anywhere (SLQA) approach providing software applications with global access to data from any node in the database network via standard SQL queries. Security policy is stored locally and enforced at the database node level, reducing potential for unauthorized data access and waste of network bandwidth. A key metric of success for a CWP project is the transition of coalition-related technology from TRL-3 or 4 to TRL-6 or higher. Thus, the end goal of this CWP project was to demonstrate the GaianDB and policy technology within an operational environment at the NATO Intelligence Fusion Centre (NIFC) at Molesworth RAF. An initial demonstration of this technology in a 'stand alone' environment was undertaken at the NIFC in November 2011 using a data set comprised of 140,000 documents. Recently the system has been modified to include a secure authentication mechanism based on a Kerberos ticketing framework and this has now been integrated onto the NIFC Battlefield Information, Collection, and Exploitation System (BICES) network. In summary, the paper discusses the CWP project; the two key technologies (i.e., Gaian Database and integrated Access Policy Decision and Enforcement mechanisms) developed within the US UK ITA research program; how these have been integrated into the NIFC BICES; and future plans for the program.

Proceedings Article | 22 May 2013 Paper

Paper

Context-rich semantic framework for effective data-to-decisions in coalition networks

Keith Grueneberg, Geeth de Mel, Dave Braines, Xiping Wang, Seraphin Calo, Tien Pham

Proceedings Volume 8742, 874202 (2013) https://doi.org/10.1117/12.2018022

KEYWORDS: Sensors, Data modeling, Data fusion, Intelligence systems, Intelligent sensors, Acoustics, Defense and security, Analytical research, Control systems, Telecommunications

Read Abstract +

Proceedings Article | 24 May 2012 Paper

Paper

Autonomous UAV persistent surveillance using bio-inspired strategies

Jerry Burman, Joao Hespanha, Upamanyu Madhow, Jason Isaacs, Sriram Venkateswaran, Tien Pham

Proceedings Volume 8389, 838917 (2012) https://doi.org/10.1117/12.920018

KEYWORDS: Unmanned aerial vehicles, Sensors, Sensor networks, Acoustics, Biomimetics, Data communications, Surveillance, Unattended ground sensors, Source localization, Environmental sensing

Read Abstract +

Proceedings Article | 24 May 2012 Paper

Paper

Intent-based resource deployment in wireless sensor networks

Geeth de Mel, Tien Pham, Paul Sullivan, Keith Grueneberg, Wamberto Vasconcelos, Tim Norman

Proceedings Volume 8389, 83890U (2012) https://doi.org/10.1117/12.919998

KEYWORDS: Acoustics, Sensor networks, Sensors, Cameras, Defense and security, Reconnaissance, Analytical research, Video, Situational awareness sensors, Network security

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Proceedings Article | 23 May 2011 Paper

Paper

Service-oriented reasoning architecture for resource-task assignment in sensor networks

Geeth de Mel, Flavio Bergamaschi, Tien Pham, Wamberto Vasconcelos, Tim Norman

Proceedings Volume 8047, 80470X (2011) https://doi.org/10.1117/12.885476

KEYWORDS: Sensors, Sensor networks, Web services, Surveillance, Unmanned aerial vehicles, Computer programming, Network security, Computer architecture, Analytical research, Standards development

Read Abstract +

Proceedings Article | 23 May 2011 Paper

Paper

Semantically enriched data for effective sensor data fusion

Geeth de Mel, Tien Pham, Thyagaraju Damarla, Wamberto Vasconcelos, Tim Norman

Proceedings Volume 8047, 80470L (2011) https://doi.org/10.1117/12.885481

KEYWORDS: Sensors, Sensor networks, Video, Video surveillance, Data fusion, Infrared radiation, Surveillance, Acoustics, Information fusion, Video processing

Read Abstract +

Proceedings Article | 23 May 2011 Paper

Paper

Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

Jerry Burman, Joao Hespanha, Upamanyu Madhow, Tien Pham

Proceedings Volume 8047, 80470Y (2011) https://doi.org/10.1117/12.882802

KEYWORDS: Sensors, Unmanned aerial vehicles, Acoustics, Sensor networks, Biomimetics, Source localization, Digital filtering, Unattended ground sensors, Algorithm development, Signal to noise ratio

Read Abstract +

A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA) Sensor Network Fabric (IBM).

Proceedings Article | 8 May 2010 Paper

Paper

Heterogeneous sensor networks: a bio-inspired overlay architecture

Jerry Burman, Joao Hespanha, Upamanyu Madhow, Daniel Klein, Jason Isaacs, Sriram Venkateswaran, Tien Pham

Proceedings Volume 7694, 76940T (2010) https://doi.org/10.1117/12.851533

KEYWORDS: Sensors, Unmanned aerial vehicles, Acoustics, Sensor networks, Biomimetics, Source localization, Cameras, Unattended ground sensors, Telecommunications, Bacteria

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Proceedings Article | 5 May 2009 Paper

Paper

Heterogeneous sensor networks: a bio-inspired overlay architecture

Jerry Burman, Joao Hespanha, Upamanyu Madhow, Daniel Klein, Tien Pham, Ananthram Swami

Proceedings Volume 7333, 73330E (2009) https://doi.org/10.1117/12.819221

KEYWORDS: Sensors, Source localization, Biomimetics, Sensor networks, Unattended ground sensors, Unmanned aerial vehicles, Algorithm development, Acoustics, Databases, Signal to noise ratio

Read Abstract +

Proceedings Article | 5 May 2009 Paper

Paper

ITA Sensor Fabric

Joel Wright, Christopher Gibson, Flavio Bergamaschi, Kelvin Marcus, Tien Pham, Ryan Pressley, Gunjan Verma

Proceedings Volume 7333, 733319 (2009) https://doi.org/10.1117/12.822470

KEYWORDS: Sensors, Sensor networks, Sensor technology, Current controlled current source, Unmanned aerial vehicles, Bromine, Information science, Intelligent sensors

Read Abstract +

Proceedings Article | 7 October 2008 Paper

Paper

A system architecture for filtering and disseminating data in sensors networks

Yosef Alayev, Amotz Bar Noy, Fangfei Chen, Iris Fermin, Tien Pham, Gavin Pearson, Thomas La Porta

Proceedings Volume 7112, 711203 (2008) https://doi.org/10.1117/12.799767

KEYWORDS: Data storage, Sensor networks, Sensors, Roads, Data modeling, Information fusion, Data fusion, Electronic filtering, Neural networks, Analytical research

Read Abstract +

Proceedings Article | 3 April 2008 Paper

Paper

Policy enabled interconnection of sensor networks using a message queue infrastructure

Dinesh Chandra Verma, Greg Cirincione, Tien Pham

Proceedings Volume 6981, 698108 (2008) https://doi.org/10.1117/12.783459

KEYWORDS: Sensors, Control systems, Intelligence systems, Sensor networks, Receivers, Information security, Network security, Defense and security, Computing systems, Data fusion

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Proceedings Article | 3 April 2008 Paper

Paper

Matching sensors to missions using a knowledge-based approach

Alun Preece, Mario Gomez, Geeth de Mel, Wamberto Vasconcelos, Derek Sleeman, Stuart Colley, Gavin Pearson, Tien Pham, Thomas La Porta

Proceedings Volume 6981, 698109 (2008) https://doi.org/10.1117/12.782648

KEYWORDS: Sensors, Intelligence systems, Unmanned aerial vehicles, Surveillance, Reconnaissance, Infrared sensors, Intelligent sensors, Forward looking infrared, Taxonomy, Prototyping

Read Abstract +

Proceedings Article | 3 April 2008 Paper

Paper

The challenge of sensor information processing and delivery within network and information science research

Gavin Pearson, Tien Pham

Proceedings Volume 6981, 698105 (2008) https://doi.org/10.1117/12.783455

KEYWORDS: Sensors, Data processing, Intelligence systems, Sensor networks, Lead, Analytical research, Data fusion, Information science, Defense and security, Network security

Read Abstract +

Proceedings Article | 11 May 2007 Paper

Paper

Acoustic sensing from small-size UAVs

Dale Robertson, Tien Pham, Harris Edge, Brian Porter, Justin Shumaker, Duane Cline

Proceedings Volume 6562, 656208 (2007) https://doi.org/10.1117/12.723691

KEYWORDS: Unmanned aerial vehicles, Acoustics, Sensors, Analytical research, Sensing systems, Global Positioning System, Protactinium, Signal detection, Remote sensing, Target detection

Read Abstract +

Proceedings Article | 19 May 2006 Paper

Paper

NATO TG-53: acoustic detection of weapon firing joint field experiment

Dale Robertson, Tien Pham, Michael Scanlon, Nassy Srour, Christian Reiff, Leng Sim, Latasha Solomon, Dorothea Thompson

Proceedings Volume 6231, 62310V (2006) https://doi.org/10.1117/12.669704

KEYWORDS: Acoustics, Sensors, Weapons, Sensor technology, Artillery, Seismic sensors, Homeland security, Unattended ground sensors, Telecommunications, Explosives

Read Abstract +

Proceedings Article | 1 September 2004 Paper

Paper

TTCP AG-6: acoustic detection and tracking of UAVs

Tien Pham, Nino Srour

Proceedings Volume 5417, (2004) https://doi.org/10.1117/12.548194

KEYWORDS: Unmanned aerial vehicles, Acoustics, Sensors, Fourier transforms, Defense and security, Signal processing, Global Positioning System, Unattended ground sensors, Array processing, Sensor networks

Read Abstract +

Proceedings Article | 9 August 2004 Paper

Paper

Algorithm for classifying multiple targets using acoustic signatures

Thyagaraju Damarla, Tien Pham, Douglas Lake

Proceedings Volume 5429, (2004) https://doi.org/10.1117/12.544523

KEYWORDS: Detection and tracking algorithms, Acoustics, Roads, Sensors, Signal detection, Analytical research, Signal to noise ratio, Scene classification, Target detection, Algorithm development

Read Abstract +

Proceedings Article | 25 August 2003 Paper

Paper

Acoustic signal processing toolbox for array processing

Tien Pham, Gene Whipps

Proceedings Volume 5096, (2003) https://doi.org/10.1117/12.488051

KEYWORDS: Sensors, Detection and tracking algorithms, Acoustics, Signal processing, Phased arrays, MATLAB, Algorithm development, Array processing, Signal to noise ratio, Analytical research

Read Abstract +

Proceedings Article | 7 August 2002 Paper

Paper

Simulation of detection and beamforming with acoustical ground sensors

D. Keith Wilson, Brian Sadler, Tien Pham

Proceedings Volume 4743, (2002) https://doi.org/10.1117/12.443525

KEYWORDS: Sensors, Detection and tracking algorithms, Signal attenuation, Atmospheric propagation, Interference (communication), Phased arrays, Optical simulations, Computer simulations, Wave propagation, Turbulence

Read Abstract +

Showing 5 of 35 publications

Proceedings Volume Editor (13)

SPIE Conference Volume | 16 June 2022

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV

SPIE Conference Volume | 5 May 2021

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III

SPIE Conference Volume | 2 June 2020

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II

SPIE Conference Volume | 22 August 2019

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications

SPIE Conference Volume | 17 July 2018

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX

Showing 5 of 13 publications

Conference Committee Involvement (30)

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI

22 April 2024 | National Harbor, Maryland, United States

Assurance and Security for AI-enabled Systems

22 April 2024 | National Harbor, Maryland, United States

SPIE Defense + Commercial Sensing

21 April 2024 | National Harbor, United States

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V

1 May 2023 | Orlando, Florida, United States

SPIE Defense + Commercial Sensing

30 April 2023 | Orlando, United States

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV

4 April 2022 | Orlando, Florida, United States

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III

12 April 2021 | Online Only, Florida, United States

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II

27 April 2020 | Online Only, California, United States

Cyber Sensing 2020

27 April 2020 | Online Only, California, United States

Cyber Sensing 2019

17 April 2019 | Baltimore, MD, United States

Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications

15 April 2019 | Baltimore, MD, United States

Cyber Sensing 2018

17 April 2018 | Orlando, FL, United States

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX

16 April 2018 | Orlando, FL, United States

Cyber Sensing 2017

11 April 2017 | Anaheim, CA, United States

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VIII

10 April 2017 | Anaheim, CA, United States

Cyber Sensing 2016

19 April 2016 | Baltimore, MD, United States

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII

18 April 2016 | Baltimore, MD, United States

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VI

20 April 2015 | Baltimore, MD, United States

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR V

5 May 2014 | Baltimore, MD, United States

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IV

29 April 2013 | Baltimore, Maryland, United States

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR III

23 April 2012 | Baltimore, Maryland, United States

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR II

26 April 2011 | Orlando, Florida, United States

Ground/Air Multi-Sensor Interoperability, Integration, and Networking for Persistent ISR

6 April 2010 | Orlando, Florida, United States

Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VIII

15 April 2009 | Orlando, Florida, United States

Unattended Ground, Sea, and Air Sensor Technologies and Applications XI

13 April 2009 | Orlando, Florida, United States

Bio-Inspired/Biomimetic Sensor Technologies and Applications

13 April 2009 | Orlando, Florida, United States

Unmanned/Unattended Sensors and Sensor Networks V

16 September 2008 | Cardiff, Wales, United Kingdom

Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VII

17 March 2008 | Orlando, Florida, United States

Unattended Ground, Sea, and Air Sensor Technologies and Applications X

17 March 2008 | Orlando, Florida, United States

Unattended Ground, Sea, and Air Sensor Technologies and Applications IX

9 April 2007 | Orlando, Florida, United States

Showing 5 of 30 Conference Committees

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