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 Narayanan, Pughazendi; Jeevan Nagendra Kumar, Y.; Chandrasekhar, Rohith Bhat; Kumaresan, Praghash Title A name given to the resource A novel wide slice kronecker forward fractional network for osteoporosis detection using knee X-ray image Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Knowledge-Based Systems;Volume;342;Issue;;Article No.;115806; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.knosys.2026.115806" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.knosys.2026.115806</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105035378381?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105035378381?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 Narayanan P., Faculty of Science and Humanities, SRM Institute of Science and Technology (Ramapuram Campus), Chennai, 600 089, India; Jeevan Nagendra Kumar Y., Department of Information Technology, Gokaraju Rangaraju Institute of Engineering and Technology, Bachupally, Hyderabad, India; Chandrasekhar R.B., Department of Computer Science and Engineering Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Tamil Nadu, Chennai, India; Kumaresan P., Department of Electronics and Communication Engineering, Christ University, Bengaluru, India Description An account of the resource Osteoporosis is an asymptomatic and progressive skeletal disorder that maximizes the risk of fractures in people aged 50 to 60. Early and accurate detection is critical, yet challenging, due to the fine structural changes in bone that are often difficult to identify in routine medical images. Knee X-rays are commonly used diagnostic tools, but interpreting them for osteoporosis detection remains complex because of variations in bone geometry and trabecular patterns. To solve these challenges, the novel Wide Slice Kronecker Forward Fractional Network (WKFF-Net) is developed to detect osteoporosis efficiently. Initially, the input image is taken from the database for detection. Here, the denoising process is done using the Non-Local Means (NLM) filter, and the Otsu thresholding method is considered for the segmentation process. Further, a template search method is used for analyzing the femur geometry. Next, features, like spatial, adaptive Local Binary Patterns (aLBP), Convolutional Neural Networks (CNN), and medical-level features, are extracted, and osteoporosis detection is accomplished by the hybrid WKFF-Net model that integrates Deep Kronecker Network (DKN), Wide Slice Residual Network (WISeR), and fractional calculus. The experimental results obtained by the WKFF-Net are 90.868% accuracy, 92.876% True Positive Rate (TPR), 87.766% True Negative Rate (TNR), 89.888% precision, and 91.357% F1-score, for 90% of the training samples. 2026 Elsevier B.V. Subject The topic of the resource Deep learning; Knee X-ray images; Non-local means filter; Ostu thresholding; Wide slice kronecker forward fractional network Publisher An entity responsible for making the resource available Elsevier B.V. Relation A related resource ISSN: 9507051; CODEN: KNSYE 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