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 Faculty Publications Article Faculty Publications -Articles 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/. Creator An entity primarily responsible for making the resource Bhimaavarapu, Krishna; Devi, Bylapudi Rama; Mahato, Chandra Bhushan; Kasireddy, Lakshmi Chandrakanth; Vadivukarassi, M.; Sivaraman, P. Title A name given to the resource An Effective IoT based Vein Recognition Using Convolutional Neural Networks and Soft Computing Techniques for Dorsal Vein Pattern Analysis Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Journal of Intelligent Systems and Internet of Things;Volume;16;Issue;2;pp.26-41 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.54216/JISIoT.160203" target="_blank" rel="noreferrer noopener">https://doi.org/10.54216/JISIoT.160203</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105001641835?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105001641835?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Bhimaavarapu K., Dept. Of CSE, Koneru Lakshmaiah Education Foundation, (Deemed to be University), Vaddeswaram, Guntur, A.P, India; Devi B.R., Dept. Of ECE, Anil Neerukonda Institute of Technology &amp; Sciences, AP, Visakhapatnam, India; Mahato C.B., MIT Muzaffarpur, Bihar, India; Kasireddy L.C., R&amp;D-Engineering, ThoughtSpot Inc, Franklin, TN, United States; Vadivukarassi M., Department of CSE, St. Martin's Engineering College, Telangana, Secunderabad, India; Sivaraman P., Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology, TN, Erode, India Description An account of the resource In this research, we provide a CNN-based system that can reliably identify the dorsal veins of the hand. In order to get better results on different picture quality datasets, the suggested model makes use of refined variants of the pre-trained VGG Net-16 and VGG Net-19 designs. We use the BOSPHORUS dataset, which provides medium-quality photos, in addition to two self-constructed datasets that provide good-and low-quality images. By using state-of-the-art augmenting image methods, streamlined pre-processing procedures, and meticulously designed CNN designs, the fine-tuned VGG Net-16 model achieves superior performance in comparison to all other models. Using ROI pictures with a resolution of 22424 pixels, a multi-class technique is employed for arranging the vein patterns. Improving data quality during training makes the approach more broad, which helps prevent over fitting. On every dataset, the proposed method achieves better results than standard ML models like K-NN and SVM, and the experimental outcomes demonstrate significant improvements in accuracy. The modifying process led to a considerable decrease in the equal error rates (EER) when compared to benchmark methods. The structure enhances efficiency in computing with GPU-accelerated studying. It was built with the help of Python extensions like as OpenCV, Keras, and TensorFlow. Results from extensive testing of the proposed method show an accuracy of 99.98%, a precision of 98.98%, and a recall of 98.8%. From what we can see, the technique is both adaptable and dependable; making it well suited for use in practical biometrics vein recognition applications. 2025, American Scientific Publishing Group (ASPG). All rights reserved. Subject The topic of the resource AI; BOSPHORUS; EER; KNN; ROI; SVM; VGG Net-16 Publisher An entity responsible for making the resource available American Scientific Publishing Group (ASPG) Relation A related resource ISSN: 2769786X; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online