Journal ArticleDOI
Recent Trends in Deep Learning Based Natural Language Processing [Review Article]
TLDR
This paper reviews significant deep learning related models and methods that have been employed for numerous NLP tasks and provides a walk-through of their evolution.Abstract:
Deep learning methods employ multiple processing layers to learn hierarchical representations of data, and have produced state-of-the-art results in many domains. Recently, a variety of model designs and methods have blossomed in the context of natural language processing (NLP). In this paper, we review significant deep learning related models and methods that have been employed for numerous NLP tasks and provide a walk-through of their evolution. We also summarize, compare and contrast the various models and put forward a detailed understanding of the past, present and future of deep learning in NLP.read more
Citations
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Journal ArticleDOI
Deep Learning for Generic Object Detection: A Survey
Li Liu,Li Liu,Wanli Ouyang,Xiaogang Wang,Paul Fieguth,Jie Chen,Xinwang Liu,Matti Pietikäinen +7 more
TL;DR: A comprehensive survey of the recent achievements in this field brought about by deep learning techniques, covering many aspects of generic object detection: detection frameworks, object feature representation, object proposal generation, context modeling, training strategies, and evaluation metrics.
Journal ArticleDOI
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Laith Alzubaidi,Jinglan Zhang,Amjad J. Humaidi,Ayad Q. Al-Dujaili,Ye Duan,Omran Al-Shamma,José Santamaría,Mohammed A. Fadhel,Muthana Al-Amidie,Laith Farhan +9 more
TL;DR: In this paper, a comprehensive survey of the most important aspects of DL and including those enhancements recently added to the field is provided, and the challenges and suggested solutions to help researchers understand the existing research gaps.
Journal ArticleDOI
Deep Learning With Edge Computing: A Review
Jiasi Chen,Xukan Ran +1 more
TL;DR: This paper will provide an overview of applications where deep learning is used at the network edge, discuss various approaches for quickly executing deep learning inference across a combination of end devices, edge servers, and the cloud, and describe the methods for training deep learning models across multiple edge devices.
Journal ArticleDOI
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
TL;DR: This work reviews the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.
Journal ArticleDOI
Towards artificial general intelligence with hybrid Tianjic chip architecture.
Jing Pei,Lei Deng,Sen Song,Sen Song,Mingguo Zhao,Youhui Zhang,Shuang Wu,Guanrui Wang,Zhe Zou,Zhenzhi Wu,Wei He,Feng Chen,Ning Deng,Si Wu,Yu Wang,Yujie Wu,Z. Yang,Cheng Ma,Guoqi Li,Wentao Han,Huanglong Li,Huaqiang Wu,Rong Zhao,Yuan Xie,Luping Shi +24 more
TL;DR: The Tianjic chip is presented, which integrates neuroscience-oriented and computer-science-oriented approaches to artificial general intelligence to provide a hybrid, synergistic platform and is expected to stimulate AGI development by paving the way to more generalized hardware platforms.
References
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Proceedings Article
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Proceedings Article
Attention is All you Need
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