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A CNN–LSTM-based deep learning model for early prediction of student’s performance Cover

A CNN–LSTM-based deep learning model for early prediction of student’s performance

International Journal on Smart Sensing and Intelligent Systems
Volume 17 (2024): Issue 1 (January 2024)
By: Monika Arya,  Anand Motwani,  Kauleshwar Prasad,  Bhupesh Kumar Dewangan,  Tanupriya Choudhury and  Piyush Chauhan  
Open Access
|Dec 2024

Authors

Monika Arya

Department of Computer Science and Engineering, CMR Engineering College, Hyderabad, India

Anand Motwani

Department of Computer Science, School of Computing Science and Engineering, VIT Bhopal University, Sehore, India

Kauleshwar Prasad

Department of Computer Science and Engineering, BIT, India

Bhupesh Kumar Dewangan

bhupesh.dewangan@opju.ac.in

Department of Computer Science and Engineering, OP Jindal University, Raigarh, India

Tanupriya Choudhury

Tanupriya@ddn.upes.ac.in

School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, India

Piyush Chauhan

piyush.chauhan@sitnagpur.siu.edu.in

Department of Computer Science and Engineering, Symbiosis Institute of Technology, Nagpur Campus, Symbiosis International (Deemed University), Pune, India
DOI: https://doi.org/10.2478/ijssis-2024-0036 | Journal eISSN: 1178-5608
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Language: English
Submitted on: Sep 10, 2024
Published on: Dec 2, 2024
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
convolutional neural network (CNN),
long short-term memory (LSTM),
deep learning,
machine learning,
Prediction
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2024 Monika Arya, Anand Motwani, Kauleshwar Prasad, Bhupesh Kumar Dewangan, Tanupriya Choudhury, Piyush Chauhan, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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