Arabic Sign Language Detection and Recognition Using Deep Learning Based-Heterogeneous Computing
| dc.contributor.author | Mohammad Haqqi Ismail محمد حقي اسماعيل | |
| dc.contributor.author | Supervised By Professor Dr. Shefa Abdulrahman Dawwd بإشراف الأستاذ الدكتورة شفاء عبد الرحمن داؤد | |
| dc.contributor.author | Supervised By Assistant Professor Dr. Fakhrulddin Hamid Ali بإشراف الأستاذ المساعد الدكتور فخر الدين حامد علي | |
| dc.date.accessioned | 2026-08-30T09:08:58Z | |
| dc.date.issued | 2022 | |
| dc.description | A Thesis Submitted to the Council of the college of Engineering University of Mosul As Partial Fulfillment of the Requirements for The Degree of Doctorate of Philosophy In Computer Engineering | |
| dc.identifier.uri | https://drcentrallibrary.uomosul.edu.iq/handle/123456789/8198 | |
| dc.language.iso | en | |
| dc.relation.ispartofseries | 5595th | |
| dc.subject | Hand Gesture | |
| dc.subject | Sign Recognition | |
| dc.subject | Sign Detection | |
| dc.subject | Heterogeneous Computing | |
| dc.subject | Deep Learning | |
| dc.title | Arabic Sign Language Detection and Recognition Using Deep Learning Based-Heterogeneous Computing | |
| dc.title.alternative | كشف وتمييز لغة الاشارة العربية باستخدام التعلم العميق للحوسبة غير المتجانسة | |
| dc.type | Thesis |
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