Ministry of Education
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Dr Shruthi U

vidwan id: 415906
Female

Assistant Professor, Department of Computer Science and Engineering
R N S Institute of Technology, BANGALORE

Orchid Icon 0000-0002-0676-3645 Google Scholar Icon 57215117446 Researcher Icon AGM-6572-2022 Google Scholar Icon u8yR6a8AAAAJ

Expertise

  • Computer Science Artificial Intelligence

Publications

Total Articles 8
Books 0
Proceedings 0

Publications

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Scopus

Citations 292
h-index 3

CrossRef

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Citations 248
h-index 4
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Professional Recognition

2016

Teacher of Excellence

K S School of Engineering and Management
2020

STPI Young IT Professional Award

CSI
2013

Teacher of Excellence

K S School of Engineering and Management
2018

Teacher of Excellence

K S School of Engineering and Management

Community & Membership

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ISTE

2012
Life Member

IEEE

2009
Student

Bio

Machine Learning, Deep Learning, Digital Image Processing

Personal Details

  • Female
  • Assistant Professor , R N S Institute of Technology, BANGALORE
  • Rajarajeshwari Nagar, Bengaluru, Karnataka, India
Ph D
Other Institute 2024
M.Tech
Other Institute 2011
BE
Other Institute 2008
Assistant Professor Jul 2023 – Present
R N S Institute of Technology, BANGALORE | Department of Computer Science and Engineering
Assistant Professor Jul 2019 – Jun 2023
Presidency University , Bengaluru | Department of Computer Science and Engineering
Assistant Professor Jul 2012 – May 2019
K S School of Engineering and Management | Department of Computer Science Engineering
Lecturer Aug 2011 – Jul 2012
Kalpataru Institute of Technology, Tiptur | Information science and engineering
Lecturer Aug 2008 – Sep 2009
Adichunchanagiri Institute of Technology, CHIKKAMAGALUR | Information Science and Engineering

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Co-Authors (3)

Raghavendra

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Presidency University , Bengaluru

Sunil

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Scholarly Work

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Al Based Humanoid Industrial Robot

Dr. Dilip Raju
Dr. Ruma Sinha
Dr. Jayachitra Govindaraju
Ms. Nishchitha Maligere Harendra Kumar
Dr. Tejashwini Nagaraj
Mr. Sunil Godabanahal Lokappa
Ms. Shruthi Umamaheswarappa
Engineering and Technology Patent No. : 6369685 Filed : 02-06-2024
Published : 02-07-2024 Granted

Scholarly Publications

TomSevNet: a hybrid CNN model for accurate tomato disease identification with severity level assessment

Open Access
Article
Year: 2024. Volume: 36 , Issue: 10 , Pages: 5165-5181 .
Authors: U. Shruthi ., V. Nagaveni .,
DOI 10.1007/s00521-023-09351-w
8 10

Improving Tomato Disease Classification Using BR-TomatoCNN: An Efficient Model Utilizing Bottleneck Residuals

Open Access
journal-article
Journal of Advances in Information Technology. Year: 2024. Volume: 15 , Issue: 8 , Pages: 903-913 .
Authors: U. Shruthi;V. Nagaveni;Sunil G. L.
DOI 10.12720/jait.15.8.903-913

Tomato plant disease classification using deep learning architectures: A review

Open Access
book chapter
Year: 2022. Pages: 153-169 .
Authors: U. Shruthi ., V. Nagaveni ., C. S. Arvind ., G. L. Sunil .,
DOI 10.1007/978-981-16-7389-4_15

A Review on Prediction of Crop Yield using Machine Learning Techniques

Open Access
conference paper
Year: 2022. Pages: 1-5 .
Authors: Sunil G L, Nagaveni V, Shruthi U,
DOI 10.1109/TENSYMP54529.2022.9864482.

Apple Varieties Classification using Light Weight CNN Model

Open Access
Conference Paper
Year: 2022. Pages: 68-72 .
Authors: U Shruthi ., Kalidindi Sai Narmadha ., E Meghana ., D N Meghana ., K P Lakana ., M P Bhuvan .,
DOI 10.1109/I4C57141.2022.10057703
5 7

A Review on Prediction of Crop Yield using Machine Learning Techniques

Open Access
conference-paper
Year: 2022.
Authors: Sunil G L;Nagaveni V;Shruthi U
DOI 10.1109/tensymp54529.2022.9864482
11

DIABETES PREDICTION USING MACHINE LEARNING TECHNIQUE

Open Access
article
Year: 2021. Volume: 3 , Pages: 2930-2936 .
Authors: U Shruthi, Talari Naveen Kumar, Allingaram Ajay, Allaparthi Charan, Adavi Dilip, Kumar Yadav, Kusetty Rupesh

A Review on Machine Learning Classification Techniques for Plant Disease Detection

Open Access
Conference Paper
Year: 2019. Pages: 281-284 .
Authors: Shruthi U.;Nagaveni V.;Raghavendra B.K.
DOI 10.1109/ICACCS.2019.8728415
224 275