Distributed artificial intelligence empowered by end-edge-cloud computing: A survey
As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …
also supports artificial intelligence evolving from a centralized manner to a distributed one …
Convergence of edge computing and deep learning: A comprehensive survey
Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …
massive amounts of data, and ever-increasing computing power is driving the core of …
[HTML][HTML] Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm …
Artificial intelligence (AI) has been heralded by many as the next source of business value.
Grounded on the resource-based theory of the firm and on recent work on AI at the …
Grounded on the resource-based theory of the firm and on recent work on AI at the …
A survey of deep learning techniques for autonomous driving
The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
Deep learning for motor imagery EEG-based classification: A review
Objectives The availability of large and varied Electroencephalogram (EEG) datasets,
rapidly advances and inventions in deep learning techniques, and highly powerful and …
rapidly advances and inventions in deep learning techniques, and highly powerful and …
Efficient acceleration of deep learning inference on resource-constrained edge devices: A review
Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted
in breakthroughs in many areas. However, deploying these highly accurate models for data …
in breakthroughs in many areas. However, deploying these highly accurate models for data …
Equivalent-accuracy accelerated neural-network training using analogue memory
Neural-network training can be slow and energy intensive, owing to the need to transfer the
weight data for the network between conventional digital memory chips and processor chips …
weight data for the network between conventional digital memory chips and processor chips …
[HTML][HTML] Computer vision algorithms and hardware implementations: A survey
X Feng, Y Jiang, X Yang, M Du, X Li - Integration, 2019 - Elsevier
The field of computer vision is experiencing a great-leap-forward development today. This
paper aims at providing a comprehensive survey of the recent progress on computer vision …
paper aims at providing a comprehensive survey of the recent progress on computer vision …
FPGA-based accelerators of deep learning networks for learning and classification: A review
Due to recent advances in digital technologies, and availability of credible data, an area of
artificial intelligence, deep learning, has emerged and has demonstrated its ability and …
artificial intelligence, deep learning, has emerged and has demonstrated its ability and …
[HTML][HTML] Tackling faults in the industry 4.0 era—a survey of machine-learning solutions and key aspects
The recent advancements in the fields of artificial intelligence (AI) and machine learning
(ML) have affected several research fields, leading to improvements that could not have …
(ML) have affected several research fields, leading to improvements that could not have …