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 LBP-GLZM Based Hybrid Model for Classification of Breast Cancer Subject The topic of the resource Augmentation; Breast Cancer; CNN; DDSM; GLZM; LBP Description An account of the resource Classifying mammogram images is difficult because of their complex backgrounds and the differences in resolutions across the images. One of the toughest parts is telling the difference between harmless (benign) and harmful (malignant) tissue. This is hard because the differences between them are incredibly subtle. As a consequence, the distinctive features embedded within tissue patches become not just relevant but critical for the accurate and automatic classification of these images. Traditionally, efforts to automate this classification process have encountered limitations when relying on a singular feature or a restricted set of characteristics. The subtle variations in texture within these images often render such approaches insufficient in achieving high-quality categorization results. Recognizing this, the present investigation undertakes a more comprehensive approach by incorporating distinct feature extraction techniques - specifically, the utilization of Local Binary Pattern (LBP) and Gray Level Zone Matrix (GLZM). These techniques are adept at capturing and delineating the nuanced texture features inherent in mammogram images. By extracting and analyzing these textural nuances, the aim is to construct a hybrid model capable of classifying mammograms into three distinct categories: malignant, benign, and without the necessity for further examination or follow-up. This proposed hybrid model holds significant promise in the field of mammography classification by leveraging the strengths and complementary attributes of multiple feature extraction methods. The integration of LBP and GLZM aims not only to enhance the accuracy of classification but also to improve the robustness of the system in identifying subtle yet crucial differences in tissue textures. Ultimately, the goal is to create a hybrid feature extraction framework that augments the diagnostic capabilities of mammography, providing more precise and reliable categorization of breast tissue for effective medical decision-making and patient care. 2024 IEEE. Creator An entity primarily responsible for making the resource Mahapatra D.; Umme Salma M. Source A related resource from which the described resource is derived Proceedings of ICWITE 2024: IEEE International Conference for Women in Innovation, Technology and Entrepreneurship, pp. 305-310. 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/ICWITE59797.2024.10503412" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICWITE59797.2024.10503412</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192560889&amp;doi=10.1109%2FICWITE59797.2024.10503412&amp;partnerID=40&amp;md5=4ef67843eb115bce4bb66789fa35b195" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192560889&amp;doi=10.1109%2fICWITE59797.2024.10503412&amp;partnerID=40&amp;md5=4ef67843eb115bce4bb66789fa35b195</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835038328-7 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 Mahapatra D., Christ (Deemed to Be University), Department of Statistics and Data Science, Karnataka, Bengaluru, India; Umme Salma M., Christ (Deemed to Be University), Department of Statistics and Data Science, Karnataka, Bengaluru, India