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In sign languages, there are numerous signs, each characterized by differences in hand shapes, hand positions, motions, facial expressions, and body parts used to convey specific meanings. The complexity of visual sign language recognition poses a significant challenge in the computer vision research area. This study presents an Arabic Sign Language recognition (ArSL) system that utilizes convolutional neural networks (CNNs) and several transfer learning models to automatically and accurately identify Arabic Sign Language characters. The dataset used for this study comprises 54,049 images of ArSL letters. The results of this research indicate that InceptionV3 outperformed other pretrained models, achieving a remarkable 100% accuracy score and a 0.00 loss score without overfitting. These impressive performance measures highlight the distinct capabilities of InceptionV3 in recognizing Arabic characters and underscore its robustness against overfitting. This enhances its potential for future research in the field of Arabic Sign Language recognition.<\/jats:p>","DOI":"10.1155\/2023\/5195007","type":"journal-article","created":{"date-parts":[[2023,12,6]],"date-time":"2023-12-06T20:20:09Z","timestamp":1701894009000},"page":"1-11","source":"Crossref","is-referenced-by-count":6,"title":["Image-Based Arabic Sign Language Recognition System Using Transfer Deep Learning Models"],"prefix":"10.1155","volume":"2023","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4722-6632","authenticated-orcid":true,"given":"Qanita","family":"Bani Baker","sequence":"first","affiliation":[{"name":"Department of Computer Science, Jordan University of Science and Technology, Irbid, Jordan"}]},{"given":"Nour","family":"Alqudah","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jordan University of Science and Technology, Irbid, Jordan"}]},{"given":"Tibra","family":"Alsmadi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jordan University of Science and Technology, Irbid, Jordan"}]},{"given":"Rasha","family":"Awawdeh","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jordan University of Science and Technology, Irbid, Jordan"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1080\/23273798.2017.1411961"},{"key":"2","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1017\/CBO9780511712203.020","article-title":"Sign Language Geography in the arab World","volume-title":"Sign languages: A Cambridge survey","author":"K. 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