Gaylord Palms Resort & Convention Center
Orlando, Florida, United States
15 - 19 April 2018
Conference DS130
Automatic Target Recognition XXVIII
show | hide
Abstract Due:
9 October 2017

Author Notification:
11 December 2017

Manuscript Due Date:
19 March 2018

show | hide
Conference Chairs
Program Committee
Program Committee continued...
Call for
This conference will emphasize all aspects relating to the modern automatic and machine assisted target and object recognition technology: concepts such as model-based object/target recognition and tracking, neural networks, wavelets, information fusion, knowledge-based methods, adaptive and learning approaches, and advanced signal and image processing concepts for detection, tracking, and recognition for sonar/acoustic, IR, radar, laser radar, multispectral and hyperspectral sensors. Papers dealing with the entire spectrum of algorithms, systems, and architecture in ATR/AOR will be considered.

In particular papers on the model-based solutions will be considered. This includes hypotheses of the initial sets of the sensor data, predictive models of the target features and their relationships, techniques of evaluations/comparisons of the predicted models with the features extracted from the data. Suggested topics also include methods of imputation of missing or sparse data and subsequent evaluation of the results.

Another extremely important challenge for ATR is the evaluation and prediction of ATR performance given the practical limitation that data sets cannot represent the extreme variability of the real world. Methods are sought that allow a rapid insertion of new targets and adaptive algorithms capable of supporting flexible and sustained employment of ATR. A key technical challenge is the development of affordable ATR solutions that employ an open architecture to provide timely hardware and software insertion.

Papers presented at this conference will be automatically considered for inclusion in an ATR Special Issue in a refereed journal. Papers are solicited in the following and related topics:

IR-based Systems
  • detection, tracking, and recognition
  • phenomenological modeling of targets and background
  • polarization diversity
  • target/object and scene segmentation
  • Performance evaluation issues.
Hyperspectral-based Systems Registration Issues
  • detection, tracking, and recognition
  • phenomenological modeling of targets and background
  • polarization and waveform adaptation
  • target/object and scene segmentation
  • Performance evaluation issues.
Radar/Laser Radar-based Systems
  • high-range resolution radar techniques
  • joint radar target tracking and classification approaches
  • ultra-wide band radar techniques
  • Doppler, polarization, and waveform diversity for target classification
  • detection, tracking, recognition, segmentation, target, and clutter modeling
  • multisensory processing and fusion
  • Performance evaluation issues.
Sonar/Acoustic and Seismic-based Systems
  • inverse scattering issues
  • direct scattering of acoustic waves
  • tomographic image formation
  • material identification
  • ultra-wide band methods for target detection and classification
  • multisensory fusion
  • biosensor systems
  • Performance evaluation issues.
New Methodologies
  • information theoretical approaches in ATR
  • distributed and centralized sensor decision making
  • model-based object recognition
  • neural networks for ATR applications
  • wavelet decomposition methods for ATR
  • machine learning approaches such as deep learning, transfer learning, dictionary learning and manifold learning applications to ATR
  • mission adaptive systems
  • data characterization
  • performance estimation and modeling
  • ATR/AOR development tools
  • ATR/AOR architecture
  • Algorithms for human detection, tracking, and activity recognition.

Special Session on Signal Processing in Sensor Arrays is being organized to address specific issues related to arrays of dipole antenna, phased array feeds, radars and telescopes. Topics of interest include but not limited to:
  • new methodologies for beamforming, searching for direction of arrival, array calibration, parameter estimation in sensor arrays, detection and classification with sensor arrays
  • Applications include (but not limited to) automotive, military, and radio astronomy.
2017 Best Paper Award Winner

Probabilistic SVM for open set automatic target recognition on high-range resolution radar data, (10202-10)
Author(s): Jason Roos, Arnab Shaw, Wright State Univ. (United States)

2017 Best Student Paper Award Winners

Automatic threshold selection for multi-class open set recognition, (10202-19)
Author(s): Matthew Scherreik, Brian D. Rigling, Wright State Univ. (United States)

Efficient generation of image chips for training deep learning networks, (10202-2)
Author(s): Sanghui Han, Alex Farfard, John Kerekes, Michael G. Gartley, Emmett J. Ientilucci, Andreas Savakis, Rochester Institute of Technology (United States); Charles Law, Matt Turek, Keith Fieldhouse, Kitware Inc. (United States); Jason Parhan, Rensselaer Polytechnic Institute (United States); Todd Rovito,j Air Force Research Lab. (United States)

These awards are made possible by the generous sponsorship from

Back to Top