25 publications with the keyword "machine learning"


#350: D. K. Ufuktepe, F. Yang, Y. M. Kassim, H. Yu, R. J. Maude, K. Palaniappan, and S. Jaeger

Deep Learning-Based Cell Detection and Extraction in Thin Blood Smears for Malaria Diagnosis

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1--6, 2021

malaria diagnosis, plasmodium falciparum, plas-modium vivax, microscopy, thin blood smear, machine learning, image analysis

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#277: J. Patman, M. Alfarhood, S. Islam, M. Lemus, P. Calyam, and K. Palaniappan

Predictive Analytics for Fog Computing using Machine Learning and GENI

IEEE INFOCOM International Workshop on Computer and Networking Experimental Research Using Testbeds (CNERT), 2018

fog computing, machine learning, predictive analytics, software-defined networking, experimental testbed

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#189: S. Jaeger, A. Karargyris, S. Candemir, L. Folio, J. Siegelman, F. Callaghan, Z. Xue, K. Palaniappan, R. Singh, S. Antani, G. Thoma, Y.-X. Wang, P.-X. Lu, and C. J. McDonald

Automatic tuberculosis screening using chest radiographs

IEEE Trans. Medical Imaging, Volume 33, pgs. 233-245, 2014

classification, features, machine learning, data mining, biomedical

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#167: S. Candemir, K. Palaniappan, and Y. S. Akgul

Multi-class regularization parameter learning for graph cut image segmentation

IEEE Int. Symposium on Biomedical Imaging (ISBI), 2013

segmentation, graph methods, chest x-ray, machine learning, biomedical

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#155: I. Ersoy, F. Bunyak, K. Palaniappan, and J. Peng

HEp-2 Cell Classification in IIF Images Using ShareBoost

Int. Conf. Pattern Recognition, 2012

cell detection, cell classification, features, texture, machine learning, data mining, biomedical

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#153: J. Peng, K. Palaniappan, S. Candemir, and G. Seetharaman

Kullback-Leibler divergence-based data fusion for target tracking

Int. Conf. Pattern Recognition, 2012

wami, tracking, fmv, features, motion, fusion, data mining, machine learning, dod

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#144: V. B. S. Prasath, F. Bunyak, P. Dale, S. R. Frazier, and K. Palaniappan

Segmentation of breast cancer tissue microarrays for computer-aided diagnosis in pathology

IEEE Healthcare Innovation Conference, 2012

histopathology, active contours, classification, features, texture, machine learning, data mining, biomedical

Abstract, Bibtex, PlainText, PDF, Google Scholar
#134: F. Bunyak, A. Hafiane, and K. Palaniappan

Histopathology tissue segmentation by combining fuzzy clustering with multiphase vector level sets

Software Tools and Algorithms for Biological Systems, Springer, pgs. 413--424, 2011

histopathology, active contours, classification, features, texture, machine learning, data mining, biomedical

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#126: J. Peng, C. Barbu, G. Seetharaman, F. Wei, X. Wu, and K. Palaniappan

ShareBoost: Boosting for multi-view learning with performance guarantees

Lecture Notes in Artificial Intelligence (ECML PKDD), Volume 6912, pgs. 597--612, 2011

machine learning, detection, classification, features, texture, data mining

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#116: S. Jaeger, K. Palaniappan, C. S. Casas-Delucchi, and M. C. Cardoso

Classification of cell cycle phases in 3D confocal microscopy using PCNA and chromocenter features

7th Indian Conference on Computer Vision, Graphics and Image Processing, 2010

cell detection, cell segmentation, cell classification, cell tracking, features, texture, machine learning, data mining, biomedical

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#115: S. Jaeger, K. Palaniappan, C. S. Casas-Delucchi, and M. C. Cardoso

Dual channel colocalization for cell cycle analysis using 3D confocal microscopy

IEEE Int. Conf. Pattern Recognition, 2010

cell detection, cell segmentation, cell classification, features, texture, machine learning, data mining, biomedical

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#89: I. Ersoy, F. Bunyak, V. Chagin, M. C. Cardoso, and K. Palaniappan

Segmentation and classification of cell cycle phases in fluorescence imaging

Lecture Notes in Computer Science (MICCAI), Volume 5762, pgs. 617--624, 2009

cell detection, cell segmentation, cell classification, features, texture, machine learning, data mining, biomedical

Abstract, Bibtex, PlainText, PDF, PubMed, DOI, Google Scholar
#92: K. Palaniappan, F. Bunyak, S. Nath, and J. Goffeney

Parallel processing strategies for cell motility and shape analysis

High-Throughput Image Reconstruction and Analysis, Artech House Publishers, pgs. 39--85, 2009

parallelization, gpu, cell detection, cell segmentation, cell tracking, machine learning, biomedical

Abstract, Bibtex, PlainText, PDF, Google Scholar
#67: C. R. Shyu, M. Klaric, G. J. Scott, A. S. Barb, C. H. Davis, and K. Palaniappan

GeoIRIS: Geospatial information retrieval and indexing system -- Content mining, semantics, modeling, and complex queries

IEEE Trans. Geoscience Remote Sensing, Volume 45, pgs. 839--852, 2007

gis, data mining, features, machine learning, parallelization, cbir

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#65: M. Klaric, G. Scott, C. Shyu, C. Davis, and K. Palaniappan

A framework for geospatial satellite imagery retrieval systems

IEEE Int. Geoscience and Remote Sensing Symposium, pgs. 2457--2460, 2006

gis, data mining, features, machine learning, visualization, remote sensing, cbir

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#54: Y. Luo, K. Palaniappan, and Y. Li

New algorithms of neural fuzzy relation systems with min-implication composition

Lecture Notes in Computer Science (Advances in Natural Computation), Volume 3612, pgs. 1132--1141, 2005

data mining, machine learning, classification

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#55: C. R. Shyu, G. Scott, M. Klaric, C. H. Davis, and K. Palaniappan

Automatic object extraction from full differential morphological profile in urban imagery for efficient object indexing and retrievals

3rd Int. Symposium on Remote Sensing and Data Fusion Over Urban Areas (URBAN 2005), Volume 36, 2005

gis, data mining, features, machine learning, shape, remote sensing, cbir

Abstract, Bibtex, PlainText, PDF, Google Scholar
#40: D. Pi and K. Palaniappan

Robustness of discrete nonlinear systems with open-closed-loop iterative learning control

1st IEEE Int. Conf. Machine Learning and Cybernetics, Volume 3, pgs. 1263--1266, 2002

data mining, machine learning, classification

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#39: Y. Zhao, X. Zhou, K. Palaniappan, and X. Zhuang

Statistical modeling for improved land cover classification

SPIE Battlespace Digitization and Network-Centric Warfare II, Volume 4741, pgs. 296--304, 2002

gis, classification, segmentation, data mining, machine learning, remote sensing

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#33: K. Palaniappan and F. Zhu

Automatic land cover classification using evolutionary algorithms and decision trees

16th IFIP World Computer Congress 2000, Proc. Int. Conf. on Intelligent Information Processing, pgs. 327--332, 2000

gis, classification, segmentation, data mining, machine learning, remote sensing

Bibtex, PlainText, Google Scholar
#32: K. Palaniappan, F. Zhu, X. Zhuang, Y. Zhao, and A. Blanchard

Enhanced binary tree genetic algorithm for automatic land cover classification

IEEE Int. Geoscience and Remote Sensing Symposium (IGARSS), Volume II, pgs. 688--692, 2000

gis, classification, segmentation, data mining, machine learning, remote sensing

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#30: F. Zhu, Y. Zhao, K. Palaniappan, X. Zhou, and X. Zhuang

Optimal Bayesian classifier for land cover classification using Landsat TM data

IEEE Int. Geoscience and Remote Sensing Symposium (IGARSS), Volume I, pgs. 447--450, 2000

gis, classification, segmentation, data mining, machine learning, remote sensing

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#28: X. Zhuang, K. Palaniappan, and R. M. Haralick

Highly robust statistical methods based on minimum-error Bayesian classification

Visual Information Representation, Communication and Image Processing, Marcel-Dekker, pgs. 415--430, 1999

classification, data mining, machine learning

Bibtex, PlainText, Google Scholar
#17: X. Zhuang, Y. Huang, K. Palaniappan, and Y. Zhao

Gaussian mixture density modeling, decomposition and applications

IEEE Trans. Image Processing, Volume 5, pgs. 1293--1302, 1996

classification, data mining, machine learning

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#13: Y. Huang, K. Palaniappan, X. Zhuang, and J. Cavanaugh

Optic flow field segmentation and motion estimation using a robust genetic partitioning algorithm

IEEE Trans. Pattern Analysis and Machine Intelligence, Volume 17, pgs. 1177--1190, 1995

motion, tracking, segmentation, image analysis, machine learning

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar