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Ashok Krishnamurthy
Researcher at University of North Carolina at Chapel Hill
Publications - 36
Citations - 437
Ashok Krishnamurthy is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 10, co-authored 35 publications receiving 305 citations. Previous affiliations of Ashok Krishnamurthy include Texas A&M Health Science Center & Renaissance Computing Institute.
Papers
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Journal ArticleDOI
Variability in the production of quantal vowels revisited
Mary E. Beckman,Tzyy-Ping Jung,Sook‐hyang Lee,Kenneth de Jong,Ashok Krishnamurthy,Stanley C. Ahalt,K. Bretonnel Cohen,Michael J. Collins +7 more
TL;DR: In this article, an algorithm for nonlinearly transforming fleshpoint positions to a new Cartesian space in which the x and y axes represent, respectively, the distance of the fleshpoint along the opposing vocal tract wall and the distance perpendicular to the tract wall, is described.
Journal ArticleDOI
Privacy preserving interactive record linkage (PPIRL).
Hye-Chung Kum,Ashok Krishnamurthy,Ashok Krishnamurthy,Ashwin Machanavajjhala,Michael K. Reiter,Stanley C. Ahalt,Stanley C. Ahalt +6 more
TL;DR: It is found that a computer-based third-party platform that can precisely control the information disclosed at the micro level and allow frequent human interaction during the linkage process, is an effective human-machine hybrid system that significantly improves on the linkage center model both in terms of privacy and utility.
Journal ArticleDOI
Fast Healthcare Interoperability Resources (FHIR) as a Meta Model to Integrate Common Data Models: Development of a Tool and Quantitative Validation Study
Emily R. Pfaff,James Champion,Robert L. Bradford,Marshall Clark,Hao Xu,Karamarie Fecho,Ashok Krishnamurthy,Steven Cox,Christopher G. Chute,Casey Overby Taylor,Stan Ahalt +10 more
TL;DR: It is believed that CAMP FHIR can serve as an alternative to implementing new CDMs on a project-by-project basis and could support rare data sharing opportunities, such as collaborations between academic medical centers and community hospitals.
Journal ArticleDOI
Social Genome: Putting Big Data to Work for Population Informatics
TL;DR: Data-intensive research using distributed, federated, person-level datasets in near real time has the potential to transform social, behavioral, economic, and health sciences--but issues around privacy, confidentiality, access, and data integration have slowed progress.
Proceedings ArticleDOI
SAU-Net: A Universal Deep Network for Cell Counting
TL;DR: This paper extends the segmentation network, U-Net with a Self-Attention module, named SAU-Net, for cell counting and designs an online version of Batch Normalization to mitigate the generalization gap caused by data augmentation in small datasets.