S
Shailesh Kumar
Researcher at National Institutes of Health
Publications - 77
Citations - 1951
Shailesh Kumar is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Feature extraction & Circadian rhythm. The author has an hindex of 21, co-authored 73 publications receiving 1841 citations. Previous affiliations of Shailesh Kumar include University of Texas at Austin & Indian Institute of Science Education and Research, Mohali.
Papers
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Journal ArticleDOI
Best-bases feature extraction algorithms for classification of hyperspectral data
TL;DR: A set of best-bases feature extraction algorithms that are simple, fast, and highly effective for classification of hyperspectral data are proposed.
Patent
Method and apparatus for recommendation engine using pair-wise co-occurrence consistency
TL;DR: PeaCoCk as discussed by the authors uses a unique blend of technologies from statistics, information theory, and graph theory to quantify and discover patterns in relationships between entities, such as products and customers, as evidenced by purchase behavior.
Journal ArticleDOI
Hierarchical Fusion of Multiple Classifiers for Hyperspectral Data Analysis
TL;DR: This paper introduces a hierarchical technique to recursively decompose a C-class problem into C_1 two-(meta) class problems, and introduces a generalised modular learning framework used to partition a set of classes into two disjoint groups called meta-classes.
Patent
Method and apparatus for retail data mining using pair-wise co-occurrence consistency
TL;DR: PeaCoCk as mentioned in this paper uses a unique blend of technologies from statistics, information theory, and graph theory to quantify and discover patterns in relationships between entities, such as products and customers, as evidenced by purchase behavior.
Journal ArticleDOI
Detection of Na+ Transporter Proteins in Urine
J. Andrew McKEE,Shailesh Kumar,Carolyn A. Ecelbarger,Patricia Fernández-Llama,James Terris,Mark A. Knepper +5 more
TL;DR: The hypothesis that membrane transporters from upstream nephron segments are normally detectable in urine is addressed and the possibility that limited or comprehensive proteomic analysis of urine samples may be useful in clinical settings is raised.