{"id":39267,"date":"2025-02-19T17:58:41","date_gmt":"2025-02-19T17:58:41","guid":{"rendered":"https:\/\/uomosul.edu.iq\/en\/engineering\/?p=39267"},"modified":"2025-02-27T10:04:53","modified_gmt":"2025-02-27T10:04:53","slug":"39267","status":"publish","type":"post","link":"https:\/\/uomosul.edu.iq\/en\/engineering\/2025\/02\/19\/39267\/","title":{"rendered":"Master thesis defense on \u201cNon-Invasive Infant Jaundice Level Estimation from Images of the Skin Using Machine Learning\u201d"},"content":{"rendered":"
\n

A Master thesis was discussed in Department of Computer Engineering\/College of Engineering at University of Mosul entitled \u201cNon-Invasive Infant Jaundice Level Estimation from Images of the Skin Using Machine Learning\u201d submitted by the student (Banan Khalid Abdulkader Al-Dabbagh) on Wednesday, Feb. 19, 2025.<\/p>\n

The study investigates a non-invasive, image-based technique for detecting and classifying neonatal jaundice severity using advanced Machine Learning (ML) technique. A new dataset of 344 images of infants with Jaundice and healthy of full-term newborns were created with four sub-datasets for classification. The research employs Deep Transfer Learning (DTL) with pre-trained models (VGG16, ResNet50, EfficientNet) and the K-Nearest Neighbors (KNN) algorithm. It also uses handcrafted techniques for feature extraction from scratch.
\nThe study introduces two to five class classifications, with the five-class approach being novel. Several experiments and scenarios were conducted to optimize the process, demonstrating that DTL-based methods achieved higher accuracy, reaching up to 97.13%, outperforming the handcrafted method and some state-of-the-art. This research highlights the potential of DTL for improving early jaundice detection and reducing infant mortality, particularly in resource-limited settings. The methodology could lead to early jaundice detection solutions for home use alongside clinical applications.<\/p>\n

\"\" \"\"<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

A Master thesis was discussed in Department of Computer Engineering\/College of Engineering at University of Mosul entitled \u201cNon-Invasive Infant Jaundice Level Estimation from Images of the Skin Using Machine Learning\u201d submitted by the student (Banan Khalid Abdulkader Al-Dabbagh) on Wednesday, Feb. 19, 2025. The study investigates a non-invasive, image-based technique for detecting and classifying neonatal jaundice severity using advanced Machine Learning (ML) technique. A new dataset of 344 images of infants with Jaundice and healthy of full-term newborns were created with four sub-datasets for classification. The research employs Deep Transfer Learning (DTL) with pre-trained models (VGG16, ResNet50, EfficientNet) and the K-Nearest [Read More]<\/a><\/p>\n","protected":false},"author":5,"featured_media":39272,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4,3],"tags":[],"class_list":["post-39267","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","category-viva"],"_links":{"self":[{"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/posts\/39267","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/comments?post=39267"}],"version-history":[{"count":2,"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/posts\/39267\/revisions"}],"predecessor-version":[{"id":39271,"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/posts\/39267\/revisions\/39271"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/media\/39272"}],"wp:attachment":[{"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/media?parent=39267"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/categories?post=39267"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/engineering\/wp-json\/wp\/v2\/tags?post=39267"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}