Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource ELCCFD: An Efficient and Enhanced Credit Card Fraud Detection using Enhanced Deep Learning Principle Subject The topic of the resource Credit Card Fraud Detection; Deep Learning AlexNet; Enhanced Learning for Credit Card Fraud Detection (ELCCFD); GBM Description An account of the resource Credit card fraud poses a serious threat to financial institutions and their customers; hence, stringent detection protocols are necessary. This study introduces an approach known as Enhanced Learning for Credit Card Fraud Detection (ELCCFD) to enhance the accuracy of credit card fraud detection. To improve the fraud detection process, the proposed method combines the strengths of Convolutional Neural Networks (CNNs), AlexNet architecture, and Gradient Boosting Machines (GBM). The proposed approach begins with cleaning up the credit card data to get useful features, then trains a Convolutional Neural Network (CNN) using AlexNet to figure out complex patterns and representations on its own. This study generates a complete set of features by merging the CNN's output with features generated using GBM. The final model is trained by using a combination of deep learning and other conventional machine learning techniques to achieve the best results. Experimental findings on benchmark datasets demonstrate the effectiveness of the ELCCFD methodology, achieving an accuracy rate of 98%. This study combines AlexNet with GBM to get a model to capture the complex patterns and is easier to understand with the feature importance analysis. With its strong accuracy and reliability, the proposed methodology offers a strong option to fight credit card fraud, and it shows the potential for actual use in financial systems. 2024 IEEE. Creator An entity primarily responsible for making the resource Potluri P.; Suneel S.; Chandra B.; Muthukumaran D.; Upadhyaya M.; Rajesh Kanna R. Source A related resource from which the described resource is derived Proceedings - 2024 5th International Conference on Image Processing and Capsule Networks, ICIPCN 2024, pp. 337-343. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICIPCN63822.2024.00062" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICIPCN63822.2024.00062</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204777453&amp;doi=10.1109%2FICIPCN63822.2024.00062&amp;partnerID=40&amp;md5=91128030d116ea138ba95c0ce43de70e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204777453&amp;doi=10.1109%2fICIPCN63822.2024.00062&amp;partnerID=40&amp;md5=91128030d116ea138ba95c0ce43de70e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835036717-1 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Potluri P., Sitarampuram Narsapuram West Godavari district, department of CSE Swarnandhra college of engineering and technology, 534275, India; Suneel S., Institute of Aeronautical Engineering, Department of CSE(Data Science), Telangana, Hyderabad, India; Chandra B., Vignan's Institute of Information Technology(A), Department of Management Studies, AP, India; Muthukumaran D., Vel Tech Rangarajan Dr. Sagunthala, R&amp;D Institute of Science and Technology, India; Upadhyaya M., University of Bahrain, College of Business Administration, Dept. of Management &amp; Marketing, Bahrain; Rajesh Kanna R., CHRIST (Deemed to be University), Department of Computer Science, India