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Comparative study of deep learning explainability and causal ai for fraud detection Cover

Comparative study of deep learning explainability and causal ai for fraud detection

Open Access
|Aug 2024

Authors

Erum Parkar

Department of Artificial Intelligence and Machine Learning, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, India

Shilpa Gite

Department of Artificial Intelligence and Machine Learning, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, India
Symbiosis Centre for Applied Artificial Intelligence, Symbiosis Institute of Technology (Pune Campus), Symbiosis International Deemed University, Pune, India

Sashikala Mishra

sashikala.mishra@sitpune.edu.in

Department of Artificial Intelligence and Machine Learning, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, India

Biswajeet Pradhan

biswajeet.pradhan@uts.edu.au

Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia

Abdullah Alamri

Department of Geology and Geophysics, College of Science, King Saud University, Riyadh, Saudi Arabia
Language: English
Submitted on: Apr 25, 2024
Published on: Aug 6, 2024
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2024 Erum Parkar, Shilpa Gite, Sashikala Mishra, Biswajeet Pradhan, Abdullah Alamri, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.