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A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services
(
Springer New York LLC
, 2019 , Article)
This papers presents a deep learning-based framework to predict crowdsourced service availability spatially and temporally. A novel two-stage prediction model is introduced based on historical spatio-temporal traces of ...
Content-based image retrieval with compact deep convolutional features
(
Elsevier B.V.
, 2017 , Article)
Convolutional neural networks (CNNs) with deep learning have recently achieved a remarkable success with a superior performance in computer vision applications. Most of CNN-based methods extract image features at the last ...
Detecting Promotion Attacks in the App Market Using Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Article)
App markets play an important role in distributing various apps to mobile users. The app market vendors provide reputation systems to assist users in finding useful and reputable apps by ranking them. Unfortunately, there ...
Applying big data methods to understanding human behavior and health
(
Frontiers Media S.A.
, 2018 , Article)
[No abstract available]
Enquiry-based learning workshop for deep learning in Middle Eastern classrooms?an action research approach
(
Routledge
, 2018 , Article)
The senior year design students and I were dismayed when my linear teaching and their habitual rote learning failed in a Middle Eastern University. The gulf between the curricular objectives and our teaching-learning methods ...
Fault and performance management in multi-cloud based NFV using shallow and deep predictive structures
(
Springer
, 2017 , Article)
Deployment of network function virtualization (NFV) over multiple clouds accentuates its advantages such as flexibility of virtualization, proximity to customers and lower total cost of operation. However, NFV over multiple ...
A meta-framework for modeling the human reading process in sentiment analysis
(
Association for Computing Machinery
, 2016 , Article)
This article introduces a sentiment analysis approach that adopts the way humans read, interpret, and extract sentiment from text. Our motivation builds on the assumption that human interpretation should lead to the most ...
Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
Detection and classification of cell nuclei in histopathology images of cancerous tissue stained with the standard hematoxylin and eosin stain is a challenging task due to cellular heterogeneity. Deep learning approaches ...
Flow-based intrusion detection algorithm for supervisory control and data acquisition systems: A real-time approach
(
John Wiley and Sons Inc
, 2021 , Article)
Intrusion detection in supervisory control and data acquisition (SCADA) systems is integral because of the critical roles of these systems in industries. However, available approaches in the literature lack representative ...
A Deep Reinforcement Learning Framework for Data Compression in Uplink NOMA-SWIPT Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
<comment< Non-orthogonal multiple access (NOMA) shall play an important role in the current and foreseeable design of 5G and beyond networks. NOMA allows multiple users to share the same time-frequency ...