Deep Learning on Computational-Resource-Limited Platforms: A Survey
المؤلفون المشاركون
Yi, Yugen
Chen, Chunlei
Zhang, Huixiang
Zhang, Peng
Dai, Jiangyan
Zhang, Huihui
Zhang, Yonghui
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-19، 19ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-03-01
دولة النشر
مصر
عدد الصفحات
19
التخصصات الرئيسية
الملخص EN
Nowadays, Internet of Things (IoT) gives rise to a huge amount of data.
IoT nodes equipped with smart sensors can immediately extract meaningful knowledge from the data through machine learning technologies.
Deep learning (DL) is constantly contributing significant progress in smart sensing due to its dramatic superiorities over traditional machine learning.
The promising prospect of wide-range applications puts forwards demands on the ubiquitous deployment of DL under various contexts.
As a result, performing DL on mobile or embedded platforms is becoming a common requirement.
Nevertheless, a typical DL application can easily exhaust an embedded or mobile device owing to a large amount of multiply and accumulate (MAC) operations and memory access operations.
Consequently, it is a challenging task to bridge the gap between deep learning and resource-limited platforms.
We summarize typical applications of resource-limited deep learning and point out that deep learning is an indispensable impetus of pervasive computing.
Subsequently, we explore the underlying reasons for the high computational overhead of DL through reviewing the fundamental concepts including capacity, generalization, and backpropagation of a neural network.
Guided by these concepts, we investigate on principles of representative research works, as well as three types of solutions: algorithmic design, computational optimization, and hardware revolution.
In pursuant to these solutions, we identify challenges to be addressed.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chen, Chunlei& Zhang, Peng& Zhang, Huixiang& Dai, Jiangyan& Yi, Yugen& Zhang, Huihui…[et al.]. 2020. Deep Learning on Computational-Resource-Limited Platforms: A Survey. Mobile Information Systems،Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1192480
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chen, Chunlei…[et al.]. Deep Learning on Computational-Resource-Limited Platforms: A Survey. Mobile Information Systems No. 2020 (2020), pp.1-19.
https://search.emarefa.net/detail/BIM-1192480
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chen, Chunlei& Zhang, Peng& Zhang, Huixiang& Dai, Jiangyan& Yi, Yugen& Zhang, Huihui…[et al.]. Deep Learning on Computational-Resource-Limited Platforms: A Survey. Mobile Information Systems. 2020. Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1192480
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1192480
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر