Dr Prabira Kumar Sethy
vidwan id: 48627
Associate Professor, Department of Electronics and Communication Engineering
Guru Ghasidas University
Expertise
- Electrical and Electronic Engineering
Publications
Publications
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Scopus
h-index
20
CrossRef
Citations
505
h-index
11
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Professional Recognition
UGC-NET IN ELECTRONIC SCIENCE
UGCCommunity & Membership
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IEEE SENIOR MEMBER
Bio
Communication Engineering, Signal Processing, Image Processing, Deep Learning
Personal Details
- Male
- Associate Professor , Guru Ghasidas University
- Department of Electronics and Communication Engineering, Guru Ghasidas Vishwavidyalaya
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Co-Authors (17)
Veer Surendra Sai University of Technology
DRIEMS University
Shri Vishnu Engineering College for Women, Vishnupur
Indian Institute of Technology (Indian School of Mines), Dhanbad
Malla Reddy College of Engineering & Technology
SRI SRI UNIVERSITY
Indian Institute of Technology Delhi
National Institute of Technology Rourkela
Vellore Institute of Technology (VIT-AP) University, Andhra Pradesh
National Institute of Technology, Delhi
Malla Reddy College of Engineering & Technology
CVR College of Engineering
Sreenidhi University
Koneru Lakshmaiah Education Foundation, Guntur
Veer Surendra Sai University of Technology
Nagaland University
Scholarly Work
Identification of Diseases and Mineral Deficiencies of Rice Plant based on Machine Learning Approach in the natural Environment
Funding Agency: Mukhyamantri Research and Innovation Fellowship Program (MRIP) Extramural Funding
PRINICIPAL INVESTIGATOR
796,000
2024 - Ongoing
Machine Automation: Making Resilient Tools and Risk Assessment Standards in Cyber Security
Study and Analysis of Maize Diseases Using Image Processing Techniques
Crop Grain Identification, Classification and Quality Inspection Using Image Processing Techniques
n4riceleaf: AN ANDROID/WEB BASED APPLICATION TO ESTIMATE NITROGEN CONCENTRATION IN RICE CROP
PRABIRA KUMAR SETHY
Scholarly Publications
Identification of wheat grain using geometrical feature and machine learning
Open AccessNitrogen Deficiency Prediction of Rice Crop Based on Convolutional Neural Network
Open AccessDeep feature based rice leaf disease identification using support vector machine
Open Access
10.1016/j.compag.2020.105527
174
293
Fruit recognition using support vector machine based on deep features
Open Access
10.33640/2405-609X.1675
16
30