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 Mohanapriya, D.; Rajalakshmi, K.; Helen Josephine, V.L.; Panneerselvam, Karthick Title A name given to the resource Novel Anchor Generation Based Residual Network for Object Tracking in Video-Surveillance Applications 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 SN Computer Science;Volume;6;Issue;2;Article No.;117; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s42979-024-03619-1" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42979-024-03619-1</a> <br /><br /><a href="https://www.scopus.com/pages/publications/85218136650?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/85218136650?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 Mohanapriya D., Department of Computer Science (SF), Sourasthra College, Tamil Nadu, Madurai, India; Rajalakshmi K., Department of Computer Applications, CMR Institute of Technology, Karnataka, Bangalore, India; Helen Josephine V.L., Business Analytics, School of Business and Management, Christ University, Karnataka, Bangalore, India; Panneerselvam K., Department of Computer Science and Engineering, KPR Institute of Engineering and Technology, Tamilnadu, Uthupalayam, 641407, India Description An account of the resource The activity of the object in question is alerted directly upon completion of an effective object tracking. Dependent on hardware support or not, a strong object tracking protocol is required for a precise object tracking application. According to these methods, tracking an object accurately within a predetermined processing time window required a significant amount of computer complexity. In contrast, a variety of quality-degrading elements, including occlusion, shifting lighting, shadows, and so on, have an adverse effect on tracking. All of these tracking shortcomings will be fixed by a revolutionary residual network based on loss operator and anchor creation. Detection of object has concerns that rely on the process of feature extraction to afford efficient quality. For this purpose a model called ResNet has been used that comprises thirty layers and hence named as Resnet-thirty. These networks are a type of Convolutional Neural Network (CNN) that contain residual connections among various layers. The various merits of these connections is the network has the capability to learn the features of global, local and intermediate in parallel. As such, the system is robust against changes in lighting. These variations in light were understood in terms of tracking objects within a changing background. The proposed work uses MOT datasets. This dataset comprises of MOT 15, MOT16, MOT17 and MOT20. The results have been found by using these datasets. Hence, it evidently outperforms in terms of precision, recall, MOTA, IDF, MOTP, SAIDF and F1 measure to track the objects. The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource Computer vision; Loss operator; Object tracking; Residual network Publisher An entity responsible for making the resource available Springer Relation A related resource ISSN: 2662995X; 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