Lawrence Hall
Lawrence Hall
Professor of Computer Science and Engineering, University of South Florida
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Cited by
Cited by
SMOTE: synthetic minority over-sampling technique
NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer
Journal of artificial intelligence research 16, 321-357, 2002
SMOTEBoost: Improving prediction of the minority class in boosting
NV Chawla, A Lazarevic, LO Hall, KW Bowyer
Knowledge Discovery in Databases: PKDD 2003: 7th European Conference on …, 2003
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
Review of MR image segmentation techniques using pattern recognition.
JC Bezdek, LO Hall, LP Clarke
Medical physics 20 (4), 1033-1048, 1993
MRI segmentation: methods and applications
LP Clarke, RP Velthuizen, MA Camacho, JJ Heine, M Vaidyanathan, ...
Magnetic resonance imaging 13 (3), 343-368, 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
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
Clustering with a genetically optimized approach
LO Hall, IB Ozyurt, JC Bezdek
IEEE Transactions on evolutionary Computation 3 (2), 103-112, 1999
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
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
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
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
Partially supervised clustering for image segmentation
AM Bensaid, LO Hall, JC Bezdek, LP Clarke
Pattern recognition 29 (5), 859-871, 1996
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
Automatically countering imbalance and its empirical relationship to cost
NV Chawla, DA Cieslak, LO Hall, A Joshi
Data Mining and Knowledge Discovery 17, 225-252, 2008
Radiomics in brain tumor: image assessment, quantitative feature descriptors, and machine-learning approaches
M Zhou, J Scott, B Chaudhury, L Hall, D Goldgof, KW Yeom, M Iv, Y Ou, ...
American Journal of Neuroradiology 39 (2), 208-216, 2018
Ensemble diversity measures and their application to thinning
RE Banfield, LO Hall, KW Bowyer, WP Kegelmeyer
Information Fusion 6 (1), 49-62, 2005
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 (4), 2005
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
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
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