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 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/. Creator An entity primarily responsible for making the resource Likitha, T.B.; Sreeja, C.S.; Sandeep, J.; Sangeetha, G.; Nijatullah, Mansoor Title A name given to the resource Tailored Garment Recommendations Using Computer Vision and Machine Learning 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 Lecture Notes in Electrical Engineering;Volume;1399 LNEE;pp.189-201 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-4430-8_13" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-4430-8_13</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105012477140?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105012477140?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 Likitha T.B., Deparment of Computer Science, Christ Deemed to Be University, Bengaluru, India; Sreeja C.S., Deparment of Computer Science, Christ Deemed to Be University, Bengaluru, India; Sandeep J., Deparment of Computer Science, Christ Deemed to Be University, Bengaluru, India; Sangeetha G., Deparment of Computer Science, Christ Deemed to Be University, Bengaluru, India; Nijatullah M., Deparment of Computer Science, Christ Deemed to Be University, Bengaluru, India Description An account of the resource In the realm of online shopping, despite the many advancements made in this specific field, the dilemma of finding the best clothing items that are right fit and meet the style preference of a consumer and avoid returns is yet to be completely solved. This problem has often resulted in customer dissatisfaction. The proposed system intends to deal with this problem by analyzing the users body size and suggesting the best fitting garment that suits their size and style with the help of advanced computer vision and machine learning technologies. This approach not only provides an improved online shopping experience with personalized recommendations, it furthermore contributes toward reducing the environmental impact caused by the return of ill-fitting clothing hence promoting sustainability. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. Subject The topic of the resource Clothing recommendations; Computer vision; Customer satisfaction; Environmental sustainability; Future of fashion; Histogram of oriented gradients (HOG); Virtual fitting rooms Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 18761100; ISBN: 978-981964429-2; Language A language of the resource English Type The nature or genre of the resource Conference paper 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