Arvind Kumar Tiwari

Orcid: 0000-0001-5837-0854

According to our database1, Arvind Kumar Tiwari authored at least 15 papers between 2015 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
Adaptive Attention Mechanisms Based Multicriteria Recommender Systems for Improved User Preference Discovery.
SN Comput. Sci., April, 2025

NSGA-II optimized deep autoencoders for enhanced multi-criteria recommendation system.
Comput. Electr. Eng., 2025

2024
Identification of COVID-19 with CT scans using radiomics and DL-based features.
Netw. Model. Anal. Health Informatics Bioinform., December, 2024

Review of Deep Learning Techniques for Neurological Disorders Detection.
Wirel. Pers. Commun., July, 2024

Correction: Prediction of Alzheimer's Using Random Forest with Radiomic Features.
Comput. Syst. Sci. Eng., 2024

Smart Security: Unmasking Face Spoofers with Advanced Decision Tree Classifier.
Proceedings of the 15th International Conference on Computing Communication and Networking Technologies, 2024

2023
Improvements in Weather Forecasting Technique Using Cognitive Internet of Things.
Comput. Syst. Sci. Eng., 2023

Prediction of Alzheimer's Using Random Forest with Radiomic Features.
Comput. Syst. Sci. Eng., 2023

Masked Face Recognition Using MobileNet V2 with Transfer Learning.
Comput. Syst. Sci. Eng., 2023

An autoencoder-based deep learning model for solving the sparsity issues of Multi-Criteria Recommender System.
Proceedings of the International Conference on Machine Learning and Data Engineering, 2023

2022
An efficient hybrid approach for the prediction of epilepsy using CNN with LSTM.
Int. J. Artif. Intell. Soft Comput., 2022

A Survey on Computational Intelligence Techniques in Learning and Memory.
Proceedings of the Computational Intelligence in Communications and Business Analytics, 2022

2021
Classification of Breast Cancer using User-Defined Weighted Ensemble Voting Scheme.
Proceedings of the IEEE Region 10 Conference, 2021

2016
Prediction of G-protein coupled receptors and their subfamilies by incorporating various sequence features into Chou's general PseAAC.
Comput. Methods Programs Biomed., 2016

2015
An efficient approach for the prediction of ion channels and their subfamilies.
Comput. Biol. Chem., 2015


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