IEEE Applied Imagery Pattern Recognition (AIPR) 2016
Imaging and Artificial Intelligence: Intersection and Synergy

Cosmos Club, Washington, D.C.
October 18-20, 2016

The limits of computational imaging, vision, and artificial intelligence (AI) are being pushed by advances such as:

1. Robotics and autonomous systems - unmanned aerial vehicles and self-driving cars
2. Big imaging datasets - in the commercial sector and across the disciplines like connectomics, deep learning, and biologically-inspired AI methods
3. Scalable and inexpensive parallel computational resources both local and in the cloud; novel display technologies

The 2016 IEEE AIPR Workshop will explore these reemerging intersections and synergies between imaging and AI, continuing the workshop’s long tradition of bringing together researchers and developers who span the disciplines and work in labs across academia, industry, and government. The Workshop Committee invites papers that present new techniques, algorithms, analysis, applications, visualizations, systems, and theoretical insights to the interplay between imaging and artificial intelligence. Student papers are eligible for the Best Student Paper award. Topics include, but are not limited to, the following:

-Image-based autonomous capabilities in transportation, medicine, robotics, manufacturing, defense, space
-Image understanding: captioning, inference, retrieval, summarization, scene modeling
-AI tools for assisted image analysis, deep learning, visualization, performance metrics and evaluation methodologies
-Medical applications: diagnosis, intervention, prognosis, telediagnostics, global health
-Biological applications: scientific discovery, high-throughput, translational potential
-Situational awareness: biometrics, surveillance, anomaly detection, environmental monitoring, video analytics, mixed and augmented reality

AIPR 2016 Program Chairs:
Prof. Murray Loew, George Washington University
Prof. Kannappan Palaniappan, University of Missouri-Columbia
email: programchair2016 at aipr-workshop dot org

Abstracts for either oral or poster presentations are now being accepted. Student papers are eligible for the Best Student Paper award. Online abstract submissions: https://cmt3.research.microsoft.com/AIPR2016

Deadline: 30 June 2016 (Extended)

Updates and additional information can be found at, http://www.aipr-workshop.org

Confirmed Keynote Speakers for 2016 include:
Jason Matheny, Director, IARPA
Christopher Rigano, Office of Science & Technology, National Institute of Justice
Joe Mundy, Brown University & Vision Systems
Steven Brumby, Descartes Labs
John Kaufhold, Deep Learning Analytics


Past Invited speakers from 2015 and 2014

AIPR 2015 Cosmos Club, Washington DC

Hal Weaver, JHU APL, New Horizons lead project scientist: “The Reconnaissance of Pluto and its Moons by NASA’s New Horizons Mission”
Herbert O. Funsten, Los Alamos National Lab: “Beyond Pluto: The Search for the Edge of the Solar System”
Jay Herman, NASA GSFC, Earth as a Planet: The View from Lagrange-1
Piers Sellers, Astronaut and Deputy Director of NASA Science and Exploration Directorate: "Help from Above: Satellites, models and the future of Planet Earth"
Marc Imhoff, NASA Emeritus: “A Satellite Supported View of Energy, Policy, and Ecosystems Services for an 11 Billion Person Planet: What's Ahead?”


AIPR 2014 Cosmos Club, Washington DC

Dr Peter Highnam, Director, IARPA, Intelligence ARPA: An Overview
Dr. Lee Schwartz, Office of the Geographer, US Department of State, The MapGive Project
Dr Nibir Dhar, Deputy Director, Night Vision Electronic Sensors Directorate, Enabling Technologies for Advanced Imaging
Robbie Schingler, COO, Planet Labs Inc.
Dr Philip Perconti, Director, US Army Research Laboratory, Vision to Perception - Imagery Analytics for Land Forces
Dr. John Scott, RIT's Chester F. Carlson Center for Imaging Science, DIRSIG
Scott Fouse, Lockheed Martin Co, California
Joshua C. Klontz. A Case Study of Automated Face Recognition: The Boston Marathon Bombings Suspects
Rama Chellappa. Persistent and Pervasive Imaging Analytics for Environmental Assessment of Oceanic Resources and Fish Stocks
Richard Granger, Dartmouth College, Beyond neural networks to brain engineering: How brains recognize, localize, search, and track