تصنيف الأزياء التقليدية السعودية باستخدام تقنية التعلم العميق

نوع المستند : Original Article

المؤلفون

1 أستاذ تکنولوجیا تصنیع الملابس، قسم الملابس والنسیج، کلیة الأقتصاد المنزلى، جامعة الملک عبد العزیز، جدة

2 جامعة الملك عبدالعزيز

المستخلص

هدفت هذه الدراسة إلى تطوير نظام لتصنيف الملابس التقليدية في المملكة العربية السعودية باستخدام الشبكات العصبية التلافيفية. تم جمع مجموعة بيانات مكونة من 339 صورة عبر 3 فئات ومعالجتها مسبقًا، بما في ذلك التطبيع والاقتصاص والتعتيم لتحسين جودة الصورة.
أنجز النظام المقترح التصنيف من خلال عملية من خطوتين: جمع مجموعة البيانات باستخدام تقنيات الذكاء الاصطناعي (AI) لجمع 339 صورة مصنفة للملابس من المملكة العربية السعودية والتي كانت بمثابة الأساس للتدريب، والتصنيف باستخدام نموذج Inception v3 CNN مع نقل التعلم.
تم إجراء الاختبار بدقة إجمالية قدرها 84.85% ، مما يدل على قدرة العارضة على تصنيف الملابس التقليدية بشكل صحيح. تم أيضًا تنفيذ مطابقة المسافة الإقليدية الموزونة لاسترداد أفضل 5 مطابقات تشابه لصور الاستعلام.
تتيح واجهة المستخدم الرسومية التنفيذ العملي وتصنيف ملابس المستخدم النهائي. تشير النتائج الواعدة إلى أن التعلم العميق قابل للتطبيق في هذا المجال. ومع ذلك، تشمل القيود حجم مجموعة البيانات الصغيرة. يتضمن العمل المستقبلي جمع مجموعة أكبر وأكثر تنوعًا من صور الملابس السعودية التقليدية لتحسين أداء التصنيف.

الكلمات الرئيسية

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