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Chapter and Conference Paper
Stereoscopic Image Quality Assessment Based on Binocular Adding and Subtracting
There has been a great concern on blind image quality assessment in the field of 2D images, however, stereoscopic image quality assessment (SIQA) is still a challenging task. In this paper, we propose an effic...
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Chapter and Conference Paper
An Image Quality Evaluation Method Based on Joint Deep Learning
The image quality plays a very important role in image processing. In this paper, we propose an image quality evaluation method based on joint deep learning (JDL). Specifically, deep belief networks (DBNs) and...
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Chapter and Conference Paper
Inferring User Profile Using Microblog Content and Friendship Network
With the rapid development of microblogs in recent years, accurate prediction of microblog user profiles is valuable for marketing, personalized recommendation, and legal investigation. Microblog users post ri...
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Chapter and Conference Paper
An End-to-End Scalable Iterative Sequence Tagging with Multi-Task Learning
Multi-task learning (MTL) models, which pool examples arisen out of several tasks, have achieved remarkable results in language processing. However, multi-task learning is not always effective when compared wi...
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Chapter and Conference Paper
Leveraging Target-Oriented Information for Stance Classification
Classifying the stance expressed in text towards specific target, namely stance detection, is a challenging task. The biggest distinction between stance detection and ordinary sentiment classification is that ...
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Article
RETRACTED ARTICLE: Quality assessment for virtual reality technology based on real scene
Virtual reality technology is a new display technology, which provides users with real viewing experience. As known, most of the virtual reality display through stereoscopic images. However, image quality will...
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Chapter and Conference Paper
Restaurant Health Inspections and Crime Statistics Predict the Real Estate Market in New York City
Predictions of apartments prices in New York City (NYC) have always been of interest to new homeowners, investors, Wall Street funds managers, and inhabitants of the city. In recent years, average prices have ...
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Chapter and Conference Paper
Gated Fusion of Discriminant Features for Caricature Recognition
Caricature recognition is a challenging problem, because there are typically geometric deformations between photographs and caricatures. It is nontrivial to learn discriminant large-margin features. To combat ...
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Article
Deep learning-based edge caching for multi-cluster heterogeneous networks
In this work, we consider a time and space evolution cache refreshing in multi-cluster heterogeneous networks. We consider a two-step content placement probability optimization. At the initial complete cache r...
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Chapter and Conference Paper
Back to the Origin: An Intelligent System for Learning Chinese Characters
Learning Chinese characters is a challenging task for both native and foreign beginners. One major reason is that most Chinese characters in writing are distinct from each other and lack of directly phonetic c...
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Chapter and Conference Paper
A Survey on Event Relation Identification
Event relation identification aims to identify relations between events in texts, including causal relation, temporal relation, sub-class relation and so on. Most of the research focuses on temporal relation a...
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Chapter and Conference Paper
A Text Correlation Algorithm for Stock Market News Event Extraction
To extract effective information in massive financial news, this paper proposes a method to calculate the correlation between text and text set by extracting structured events in the stock market news text, an...
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Chapter and Conference Paper
An Intelligent Multimodal Dictionary for Chinese Character Learning
Chinese character learning is difficult, as the character’s definitions in dictionary are simple but abstract. The image representations of Chinese character’s definitions are easy to understand and helpful to...
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Article
Open AccessWhen Research Topic Trend Prediction Meets Fact-Based Annotations
The unprecedented growth of publications in many research domains brings the great convenience for tracing and analyzing the evolution and development of research topics. Despite the significant contributions ...
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Article
Attention-based deep convolutional neural network for spectral efficiency optimization in MIMO systems
Spectral efficiency (SE) optimization in massive multiple input multiple output (MIMO) antenna cognitive systems is a challenge originated from the coexistence restrictions. Traditional power allocation can op...
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Article
Retraction Note: Quality assessment for virtual reality technology based on real scene