Deep Learning: Concepts, Types, Applications, and Implementation
محل انتشار: مجله نظریه تقریب و کاربرد، دوره: 16، شماره: 2
سال انتشار: 1401
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 93
نسخه کامل این مقاله ارائه نشده است و در دسترس نمی باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_MSJI-16-2_011
تاریخ نمایه سازی: 28 فروردین 1402
چکیده مقاله:
Today, deep learning has attracted attention in various scientific and non-scientific fields. Deep learning is a branch of machine learning that simulates the human brain for various applications like recognizing voice, face, handwriting, identifying kinship, image processing, and etc. In deep learning, a set of representation algorithms is used to model high-level abstract concepts through learning at different levels and layers. Deep learning has become popular due to its capabilities like automatic feature extraction, high extendibility, and wide application in different fields. In this paper, it is tried to describe different deep learning models and architectures, how they are trained, and the required hardware and software structures.
کلیدواژه ها:
نویسندگان
Fereshteh Aghabeigi
Department of Computer Engineering and Information Technology- Arak Branch- Islamic Azad University- Arak- Iran.
Sara Nazari
Department of Computer Engineering and Information Technology- Arak Branch- Islamic Azad University- Arak-Iran.
Nafiseh Osati Iraqi
Department of Computer Engineering and Information Technology- Arak Branch- Islamic Azad University- Arak-Iran.