SM

sushanta kumar mohanty

Ph. D Research Scholar at Indian School of Business Management and Administration (ISBM)
📚 Research scholar | Cuttack, Odisha, India
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Information Security Network Security Information Systems VPN Network Security Cloud Computing (AWS cloud) Cyber Intrusion Monitoring Network Administration Vulnerability Scanning Windows (WIN-10 WIN-11) Ubuntu C C++ VB.net Java HTML JavaScript CSS ASP.NET PHP Oracle MS-Access MySQL Internet Networking Web Design

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Ph. D Research Scholar

Indian School of Business Management and Administration (ISBM) · January 2022 - Present
research on design of light weight model/frame work for leaf disease detection using AI

Academic Counsellor & Asst.co-ordinator

OSOU – JKBK College · -

FACULTY

IT Ravenshaw HSS Cuttack · -

Lecturer

ABIT College · January 2009 - December 2015

🎓 Education

ISBM University, Chhattisgarh

Ph.D. Computer Science in · Pursuing

IGNOU, Ravenshaw College

CIC in ·

Ravenshaw University

M.Sc. Computer Science in ·

Council of Higher Secondary Education [C.H.S.E.]

+2 in ·

Board of Secondary Education [B.S.E]

H.S.C. in ·
Description (between 50 and 1500 characters)

📚 Publications (2)

Journal: Journal of Emerging Technologies and Innovative Research • October 2025
Leaf diseases pose a significant challenge for farmers, as they can reduce crop yields and threaten food security. In the past,manual inspection was used to detect these illnesses, which may be a time...
Classifying leaf diseases have surfaced with the development of machine learning (ML) And deep learning (DL) Providing more accurate and effective treatments.This research explores the use of a variety of Machine learning and deep learning techniques Such as neural networks Random forests And support vector machines (SVM). Additionally It highlights advanced techniques such as convolutional neural networks (CNNs) and transfer learning.
Journal: Advanced International Journal for Research (AIJFR) • March 2026
One of the most significant staple crops that are consumed globally is rice (Oryaza sativa), and to avoid losses in its production and to maintain food security, it is necessary to timely identify dis...
Hybrid CNN-Transformer Attention Network (HRT-ADNet) will be proposed to achieve robust detection and classification of rice disease.
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