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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 ...
Data-driven curation, learning and analysis for inferring evolving IoT botnets in the wild
(
Association for Computing Machinery
, 2019 , Conference Paper)
The insecurity of the Internet-of-Things (IoT) paradigm continues to wreak havoc in consumer and critical infrastructure realms. Several challenges impede addressing IoT security at large, including, the lack of IoT-centric ...
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 ...
Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: Application to children with asthma
(
BioMed Central Ltd.
, 2019 , Article)
Background: Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. Recently, deep learning models ...
RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database
(
Elsevier B.V.
, 2019 , Article)
The omnipresence of unmanned aerial vehicles, or drones, among civilians can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented. Security agencies are in continuous ...
Glandular structure-guided classification of microscopic colorectal images using deep learning
(
Elsevier Ltd
, 2019 , Article)
In this work, we propose to automate the pre-cancerous tissue abnormality analysis by performing the classification of image patches using a novel two-stage convolutional neural network (CNN) based framework. Rather than ...
Fault and performance management in multi-cloud virtual network services using AI: A tutorial and a case study
(
Elsevier B.V.
, 2019 , Article)
Carriers find Network Function Virtualization (NFV) and multi-cloud computing a potent combination for deploying their network services. The resulting virtual network services (VNS) offer great flexibility and cost advantages ...
Investigating 3D holoscopic visual content upsampling using super-resolution for cultural heritage digitization
(
Elsevier B.V.
, 2019 , Article)
Through this paper, we aim at investigating the impact of using deep learning-based technologies such as super-resolution on Holoscopic 3D (H3D) images. Holoscopic 3D imaging is a technology that aims at providing ...
The research on detection of crop diseases ranking based on transfer learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Crop diseases are a major global threat to food security. Because the lack of agriculture experts or necessary facilities, it is difficult to determine the type of disease, as well as the degree of disease in time, which ...
Digital heritage enrichment through artificial intelligence and semanticweb technologies
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Art and culture represent substantial ways to transfer the history of humans across civilizations and epochs. Preserving artwork and cultural objects is thus important and the focus of multiple institutions and governments ...