| Underwater target classification in synthetic aperture sonar imagery using deep convolutional neural networks DP Williams 2016 23rd international conference on pattern recognition (ICPR), 2497-2502, 2016 | 169 | 2016 |
| On semi-supervised classification B Krishnapuram, D Williams, Y Xue, L Carin, M Figueiredo, A Hartemink Advances in neural information processing systems 17, 2004 | 162 | 2004 |
| On classification with incomplete data D Williams, X Liao, Y Xue, L Carin, B Krishnapuram IEEE transactions on pattern analysis and machine intelligence 29 (3), 427-436, 2007 | 134 | 2007 |
| Mine classification with imbalanced data DP Williams, V Myers, MS Silvious IEEE Geoscience and Remote Sensing Letters 6 (3), 528-532, 2009 | 126 | 2009 |
| On optimal AUV track-spacing for underwater mine detection DP Williams 2010 IEEE International Conference on Robotics and Automation, 4755-4762, 2010 | 108 | 2010 |
| A real-time underwater object detection algorithm for multi-beam forward looking sonar E Galceran, V Djapic, M Carreras, DP Williams IFAC Proceedings Volumes 45 (5), 306-311, 2012 | 95 | 2012 |
| Fast target detection in synthetic aperture sonar imagery: A new algorithm and large-scale performance analysis DP Williams IEEE Journal of Oceanic Engineering 40 (1), 71-92, 2014 | 94 | 2014 |
| Incomplete-data classification using logistic regression D Williams, X Liao, Y Xue, L Carin Proceedings of the 22nd International Conference on Machine learning, 972-979, 2005 | 91 | 2005 |
| On the use of tiny convolutional neural networks for human-expert-level classification performance in sonar imagery DP Williams IEEE journal of oceanic engineering 46 (1), 236-260, 2020 | 82 | 2020 |
| The Mondrian detection algorithm for sonar imagery DP Williams IEEE Transactions on Geoscience and Remote Sensing 56 (2), 1091-1102, 2017 | 76 | 2017 |
| Exploiting environmental information for improved underwater target classification in sonar imagery DP Williams, E Fakiris IEEE Transactions on Geoscience and Remote Sensing 52 (10), 6284-6297, 2014 | 76 | 2014 |
| Fast unsupervised seafloor characterization in sonar imagery using lacunarity DP Williams IEEE transactions on Geoscience and Remote Sensing 53 (11), 6022-6034, 2015 | 72 | 2015 |
| Bayesian data fusion of multiview synthetic aperture sonar imagery for seabed classification DP Williams IEEE Transactions on Image Processing 18 (6), 1239-1254, 2009 | 71 | 2009 |
| Automatic target recognition for mine countermeasure missions using forward-looking sonar data N Palomeras, T Furfaro, DP Williams, M Carreras, S Dugelay IEEE Journal of Oceanic Engineering 47 (1), 141-161, 2021 | 62 | 2021 |
| AUV-enabled adaptive underwater surveying for optimal data collection DP Williams Intelligent Service Robotics 5 (1), 33-54, 2012 | 46 | 2012 |
| Detection rate statistics in synthetic aperture sonar images J Groen, E Coiras, D Williams Proc. Intl. Conf. & Exh. Underwater Acoustic Measurements, 367-374, 2009 | 41 | 2009 |
| Adaptive multiview target classification in synthetic aperture sonar images using a partially observable Markov decision process V Myers, DP Williams IEEE Journal of Oceanic Engineering 37 (1), 45-55, 2011 | 40 | 2011 |
| Adaptive underwater sonar surveys in the presence of strong currents DP Williams, F Baralli, M Micheli, S Vasoli 2016 IEEE International Conference on Robotics and Automation (ICRA), 2604-2611, 2016 | 37 | 2016 |
| Passive acoustic surveillance of surface vessels using tridimensional array on an underwater glider A Tesei, R Been, D Williams, B Cardeira, D Galletti, D Cecchi, B Garau, ... OCEANS 2015-Genova, 1-8, 2015 | 37 | 2015 |
| A fast physics-based, environmentally adaptive underwater object detection algorithm DP Williams, J Groen OCEANS 2011 IEEE-Spain, 1-7, 2011 | 33 | 2011 |
Xuejun LiaoSAS Institue Inc., Duke UniversityZweryfikowany adres z duke.edu