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Institution

Sambalpur University

EducationSambalpur, Orissa, India
About: Sambalpur University is a education organization based out in Sambalpur, Orissa, India. It is known for research contribution in the topics: Dielectric & Population. The organization has 929 authors who have published 1657 publications receiving 19732 citations.


Papers
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Journal ArticleDOI

1,365 citations

Journal ArticleDOI
19 Apr 2004-Talanta
TL;DR: Increased utilization of mechanically stable synthetic matrices particularly silica gel as a solid support and its surface modification by impregnation of organic ligands directly or covalent grafting through spacer unit for extractive concentration of trace elements are highlighted in the present article.

860 citations

Journal ArticleDOI
TL;DR: Two interesting subclasses of normalized analytic and univalent functions in the open unit disk whose inverse has univalently analytic continuation to U is introduced and investigated.

532 citations

Journal ArticleDOI
01 Jan 2020
TL;DR: The deep feature plus support vector machine (SVM) based methodology is suggested for detection of coronavirus infected patient using X-ray images and the method is beneficial for the medical practitioner to classify among the COVID-19 patient, pneumonia patient and healthy people.
Abstract: The detection of coronavirus (COVID-19) is now a critical task for the medical practitioner The coronavirus spread so quickly between people and approaches 100,000 people worldwide In this consequence, it is very much essential to identify the infected people so that prevention of spread can be taken In this paper, the deep feature plus support vector machine (SVM) based methodology is suggested for detection of coronavirus infected patient using X-ray images For classification, SVM is used instead of deep learning based classifier, as the later one need a large dataset for training and validation The deep features from the fully connected layer of CNN model are extracted and fed to SVM for classification purpose The SVM classifies the corona affected X-ray images from others The methodology consists of three categories of Xray images, i e , COVID-19, pneumonia and normal The method is beneficial for the medical practitioner to classify among the COVID-19 patient, pneumonia patient and healthy people SVM is evaluated for detection of COVID-19 using the deep features of different 13 number of CNN models The SVM produced the best results using the deep feature of ResNet50 The classification model, i e ResNet50 plus SVM achieved accuracy, sensitivity, FPR and F1 score of 95 33%,95 33%,2 33% and 95 34% respectively for detection of COVID-19 (ignoring SARS, MERS and ARDS) Again, the highest accuracy achieved by ResNet50 plus SVM is 98 66% The result is based on the Xray images available in the repository of GitHub and Kaggle As the data set is in hundreds, the classification based on SVM is more robust compared to the transfer learning approach Also, a comparison analysis of other traditional classification method is carried out The traditional methods are local binary patterns (LBP) plus SVM, histogram of oriented gradients (HOG) plus SVM and Gray Level Co-occurrence Matrix (GLCM) plus SVM In traditional image classification method, LBP plus SVM achieved 93 4% of accuracy

250 citations

Journal ArticleDOI
TL;DR: The polycrystalline sample of NaBa2V5O15 (NBV), a member of tungsten bronze family, is prepared by a mixed oxide-technique and X-ray diffraction analysis shows the formation of single phase compound with an orthorhombic structure at room temperature.

247 citations


Authors

Showing all 949 results

NameH-indexPapersCitations
Ganapati Panda463568888
Amiya Nayak453707106
Bijay K. Mishra392165713
Amaresh Mishra389311071
Anil K. Mishra383004907
Utpal Sarkar342284468
Ashok Kumar Mishra332203915
Soumyadipta Basu311084070
Rama K. Mishra26962157
P. K. Sahoo251762597
Pradeep Kumar Naik241151734
Amarendra Narayan Misra24692511
Arun K. Pujari241222812
Sukalyan Dash241372682
S. K. Tripathy241031381
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202315
202220
2021175
2020139
2019137
2018127