K
Keshab K. Parhi
Researcher at University of Minnesota
Publications - 768
Citations - 21763
Keshab K. Parhi is an academic researcher from University of Minnesota. The author has contributed to research in topics: Decoding methods & Adaptive filter. The author has an hindex of 68, co-authored 749 publications receiving 20097 citations. Previous affiliations of Keshab K. Parhi include University of California, Berkeley & University of Warwick.
Papers
More filters
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Pipeline interleaving and parallelism in recursive digital filters. I. Pipelining using scattered look-ahead and decomposition
TL;DR: Based on the scattered look-ahead technique, fully pipelined and fully hardware efficient linear bidirectional systolic arrays for recursive digital filters are presented and the decomposition technique is extended to time-varying recursive systems.
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Seizure prediction with spectral power of EEG using cost-sensitive support vector machines
TL;DR: A patient‐specific algorithm for seizure prediction using multiple features of spectral power from electroencephalogram (EEG) and support vector machine (SVM) classification is proposed.
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DREAM: diabetic retinopathy analysis using machine learning.
TL;DR: A novel two-step hierarchical classification approach is proposed where the nonlesions or false positives are rejected in the first step and the bright lesions areclassified as hard exudates and cotton wool spots, and the red lesions are classified as hemorrhages and micro-aneurysms.
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Blood Vessel Segmentation of Fundus Images by Major Vessel Extraction and Subimage Classification
TL;DR: The proposed algorithm is less dependent on training data, requires less segmentation time and achieves consistent vessel segmentation accuracy on normal images as well as images with pathology when compared to existing supervised segmentation methods.
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Iterative Vessel Segmentation of Fundus Images
TL;DR: A novel stopping criterion is presented that terminates the iterative process leading to higher vessel segmentation accuracy and is robust to the rate of new vessel pixel addition.