Megha Bhushan

Orcid: 0000-0003-4309-875X

According to our database1, Megha Bhushan authored at least 13 papers between 2018 and 2024.

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

Timeline

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Bibliography

2024
An ontological knowledge-based method for handling feature model defects due to dead feature.
Eng. Appl. Artif. Intell., 2024

Open Science principles in software product lines: The case of the UVL ecosystem.
Proceedings of the 28th ACM International Systems and Software Product Line Conference, 2024

2023
A comparative study of machine learning and deep learning algorithms for predicting student's academic performance.
Int. J. Syst. Assur. Eng. Manag., December, 2023

Machine learning and deep learning techniques for the analysis of heart disease: a systematic literature review, open challenges and future directions.
Artif. Intell. Rev., December, 2023

Classifying breast cancer using transfer learning models based on histopathological images.
Neural Comput. Appl., July, 2023

Machine learning and deep learning approach for medical image analysis: diagnosis to detection.
Multim. Tools Appl., July, 2023

Effective Tumor Diagnosis based on Shape and Size of Tumor.
Proceedings of the 14th International Conference on Computing Communication and Networking Technologies, 2023

2022
Big Five Personality Traits Prediction Using Brain Signals.
Int. J. Fuzzy Syst. Appl., 2022

Content Based Movie Recommendation System.
Proceedings of the IEEE International Conference on Service Operations and Logistics, 2022

2021
Classifying and resolving software product line redundancies using an ontological first-order logic rule based method.
Expert Syst. Appl., 2021

2020
A classification and systematic review of product line feature model defects.
Softw. Qual. J., 2020

2018
Analyzing inconsistencies in software product lines using an ontological rule-based approach.
J. Syst. Softw., 2018

Improving quality of software product line by analysing inconsistencies in feature models using an ontological rule-based approach.
Expert Syst. J. Knowl. Eng., 2018


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