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V. N. Manjunath Aradhya
Researcher at Sri Jayachamarajendra College of Engineering
Publications - 95
Citations - 629
V. N. Manjunath Aradhya is an academic researcher from Sri Jayachamarajendra College of Engineering. The author has contributed to research in topics: Feature extraction & Probabilistic neural network. The author has an hindex of 13, co-authored 91 publications receiving 491 citations. Previous affiliations of V. N. Manjunath Aradhya include Dayananda Sagar College of Engineering & University of Mysore.
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Journal ArticleDOI
Multilingual OCR system for South Indian scripts and English documents: An approach based on Fourier transform and principal component analysis
TL;DR: This paper presents a multilingual character recognition system for printed South Indian scripts (Kannada, Telugu, Tamil and Malayalam) and English documents based on Fourier transform and principal component analysis (PCA), which are two commonly used techniques of image processing and recognition.
Proceedings ArticleDOI
Robust Unconstrained Handwritten Digit Recognition using Radon Transform
TL;DR: A novel system based on radon transform for handwritten digit recognition is proposed which represents an image as a collection of projections along various directions and a nearest neighbor classifier is used for the subsequent recognition purpose.
Journal ArticleDOI
One-shot Cluster-Based Approach for the Detection of COVID-19 from Chest X-ray Images.
TL;DR: In this paper, a cluster-based one-shot learning is introduced for detecting COVID-19 from chest X-ray images, which has an advantage of learning from a few samples against learning from many samples in case of deep leaning architectures.
Proceedings ArticleDOI
Isolated Handwritten Kannada and Tamil Numeral Recognition: A Novel Approach
TL;DR: The projection distance metric and zoning based scheme for numeral recognition and a nearest neighbor classifier is used for subsequent purpose and gives around 93% and 90% of recognition accuracy for Kannada and Tamil numerals respectively.
Posted ContentDOI
One Shot Cluster Based Approach for the Detection of COVID-19 from Chest X-Ray Images
TL;DR: Experiments conducted with publicly available chest x-ray images demonstrate that the proposed one shot cluster based approach for the accurate detection of COVID-19 accurately with high precision outperformed many of the convolutional neural network based existing methods proposed in the literature.