Lawrence Hall

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Citations	30864	15873
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Dmitry GoldgofProfessor of Computer Science and Engineering, University of South Florida, Moffitt Cancer CenterVerified email at mail.usf.edu
Kevin W. BowyerSchubmehl-Prein Family Professor of Computer Science and Engineering, University of Notre DameVerified email at nd.edu
Robert GilliesChair of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer CenterVerified email at moffitt.org
William Philip KegelmeyerSandia National LaboratoriesVerified email at sandia.gov
Nitesh V ChawlaFrank Freimann Professor of Computer Science & Engg., Notre DameVerified email at nd.edu
James C. BezdekUniversity of Melbourne, Computer and Information SystemsVerified email at unimelb.edu.au
Steven EschrichMoffitt Cancer CenterVerified email at moffitt.org
Yoganand (Yoga) BalagurunathanMoffitt Cancer CenterVerified email at moffitt.org
Matthew B. Schabath, Ph.D.H. Lee Moffitt Cancer Center & Research InstituteVerified email at moffitt.org
Kurt KramerLarcos AquacultureVerified email at larcosaqua.com
Virendra KumarAdditional Professor, Department of NMR, All India Institute of Medical SciencesVerified email at aiims.edu
Mu ZhouStanford UniversityVerified email at stanford.edu
peter moutonVerified email at disector.com
Andrew RemsenBureau of Ocean Energy ManagementVerified email at boem.gov
Rahul PaulMassachusetts General Hospital, Harvard Medical SchoolVerified email at mail.usf.edu
Prodip HoreDirector of Machine Learning & AI at American ExpressVerified email at aexp.com
Samuel HawkinsMoffitt Cancer CenterVerified email at mail.usf.edu
Hady Ahmady PhouladyCalifornia State University, SacramentoVerified email at csus.edu
Dmitry CherezovPhDVerified email at usf.edu
Hamidreza FarhidzadehPhD in Computer Science and EngineeringVerified email at mail.usf.edu

Lawrence Hall

Professor of Computer Science and Engineering, University of South Florida

Verified email at mail.usf.edu

artificial intelligence pattern recognition data mining fuzzy sets


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SMOTE: synthetic minority over-sampling technique NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer Journal of artificial intelligence research 16, 321-357, 2002	12849	2002
SMOTEBoost: Improving prediction of the minority class in boosting NV Chawla, A Lazarevic, LO Hall, KW Bowyer European conference on principles of data mining and knowledge discovery …, 2003	1381	2003
Review of MR image segmentation techniques using pattern recognition JC Bezdek, LO Hall, LP Clarke MEDICAL PHYSICS-LANCASTER PA- 20, 1033-1033, 1993	1364	1993
Radiomics: the process and the challenges V Kumar, Y Gu, S Basu, A Berglund, SA Eschrich, MB Schabath, K Forster, ... Magnetic resonance imaging 30 (9), 1234-1248, 2012	1096	2012
MRI segmentation: methods and applications LP Clarke, RP Velthuizen, MA Camacho, JJ Heine, M Vaidyanathan, ... Magnetic resonance imaging 13 (3), 343-368, 1995	994	1995
A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain LO Hall, AM Bensaid, LP Clarke, RP Velthuizen, MS Silbiger, JC Bezdek IEEE transactions on neural networks 3 (5), 672-682, 1992	756	1992
Automatic tumor segmentation using knowledge-based techniques MC Clark, LO Hall, DB Goldgof, R Velthuizen, FR Murtagh, MS Silbiger IEEE transactions on medical imaging 17 (2), 187-201, 1998	639	1998
Clustering with a genetically optimized approach LO Hall, IB Ozyurt, JC Bezdek IEEE Transactions on Evolutionary computation 3 (2), 103-112, 1999	571	1999
Validity-guided (re) clustering with applications to image segmentation AM Bensaid, LO Hall, JC Bezdek, LP Clarke, ML Silbiger, JA Arrington, ... IEEE Transactions on fuzzy systems 4 (2), 112-123, 1996	519	1996
A comparison of decision tree ensemble creation techniques RE Banfield, LO Hall, KW Bowyer, WP Kegelmeyer IEEE transactions on pattern analysis and machine intelligence 29 (1), 173-180, 2006	476	2006
Fuzzy c-means algorithms for very large data TC Havens, JC Bezdek, C Leckie, LO Hall, M Palaniswami IEEE Transactions on Fuzzy Systems 20 (6), 1130-1146, 2012	431	2012
Partially supervised clustering for image segmentation AM Bensaid, LO Hall, JC Bezdek, LP Clarke Pattern recognition 29 (5), 859-871, 1996	362	1996
Automatic segmentation of non-enhancing brain tumors in magnetic resonance images LM Fletcher-Heath, LO Hall, DB Goldgof, FR Murtagh Artificial intelligence in medicine 21 (1-3), 43-63, 2001	334	2001
MRI segmentation using fuzzy clustering techniques MC Clark, LO Hall, DB Goldgof, LP Clarke, RP Velthuizen, MS Silbiger IEEE Engineering in Medicine and Biology Magazine 13 (5), 730-742, 1994	276	1994
Ensemble diversity measures and their application to thinning RE Banfield, LO Hall, KW Bowyer, WP Kegelmeyer Information Fusion 6 (1), 49-62, 2005	257	2005
Fast accurate fuzzy clustering through data reduction S Eschrich, J Ke, LO Hall, DB Goldgof IEEE transactions on fuzzy systems 11 (2), 262-270, 2003	256	2003
Automatically countering imbalance and its empirical relationship to cost NV Chawla, DA Cieslak, LO Hall, A Joshi Data Mining and Knowledge Discovery 17 (2), 225-252, 2008	250	2008
Active learning to recognize multiple types of plankton T Luo, K Kramer, DB Goldgof, LO Hall, S Samson, A Remsen, T Hopkins Journal of Machine Learning Research 6 (Apr), 589-613, 2005	247	2005
Knowledge-based classification and tissue labeling of MR images of human brain C Li, DB Goldgof, LO Hall IEEE transactions on Medical Imaging 12 (4), 740-750, 1993	247	1993
Reproducibility and prognosis of quantitative features extracted from CT images Y Balagurunathan, Y Gu, H Wang, V Kumar, O Grove, S Hawkins, J Kim, ... Translational oncology 7 (1), 72-87, 2014	224	2014

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