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Kai Feng, Xitian Pi, Hongying Liu and Kai Sun
Myocardial infarction is one of the most threatening cardiovascular diseases for human beings. With the rapid development of wearable devices and portable electrocardiogram (ECG) medical devices, it is possible and conceivable to detect and monitor myoca...
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Min Zhang and Guohua Geng
Social media and health-related forums, including the expression of customer reviews, have recently provided data sources for adverse drug reaction (ADR) identification research. However, in the existing methods, the neglect of noise data and the need fo...
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Fekhr Eddine Keddous and Amir Nakib
Convolutional neural networks (CNNs) have powerful representation learning capabilities by automatically learning and extracting features directly from inputs. In classification applications, CNN models are typically composed of: convolutional layers, po...
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Kun Fan, Chungin Joung and Seungjun Baek
Video prediction which maps a sequence of past video frames into realistic future video frames is a challenging task because it is difficult to generate realistic frames and model the coherent relationship between consecutive video frames. In this paper,...
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Yepeng Cheng, Zuren Liu and Yasuhiko Morimoto
Traditional time series forecasting techniques can not extract good enough sequence data features, and their accuracies are limited. The deep learning structure SeriesNet is an advanced method, which adopts hybrid neural networks, including dilated causa...
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Zhongyan Liu, Jiangtao Mei, Deguo Wang, Yanbao Guo and Lei Wu
As a new type of riser connecting offshore platforms and submarine pipelines, steel catenary risers (SCRs) are generally subject to waves and currents for a long time, thus it is significant to fully evaluate the SCR structure?s safety. Aiming at the dam...
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Ziwen Gao, Zhiyi Li, Jiaying Luo and Xiaolin Li
This paper describes the construction a short-text aspect-based sentiment analysis method based on Convolutional Neural Network (CNN) and Bidirectional Gating Recurrent Unit (BiGRU). The hybrid model can fully extract text features, solve the problem of ...
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Waleed Albattah and Saleh Albahli
Handwritten character recognition is a computer-vision-system problem that is still critical and challenging in many computer-vision tasks. With the increased interest in handwriting recognition as well as the developments in machine-learning and deep-le...
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Dahye Kim, YoungJin Kim and Young-Seob Jeong
We make daily comments on online platforms (e.g., social networks), and such natural language texts often contain sentiment (e.g., positive and negative) for certain aspects (e.g., food and service). If we can automatically extract the aspect-based senti...
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Zhangfang Hu, Libujie Chen, Yuan Luo and Jingfan Zhou
The proposed method in this study can be used in EEG emotion recognition and achieve better results.
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Guillaume Coiffier, Ghouthi Boukli Hacene and Vincent Gripon
Deep Neural Networks are state-of-the-art in a large number of challenges in machine learning. However, to reach the best performance they require a huge pool of parameters. Indeed, typical deep convolutional architectures present an increasing number of...
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Chang-Min Kim, Ellen J. Hong, Kyungyong Chung and Roy C. Park
As people communicate with each other, they use gestures and facial expressions as a means to convey and understand emotional state. Non-verbal means of communication are essential to understanding, based on external clues to a person?s emotional state. ...
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Wenkuan Li, Peiyu Liu, Qiuyue Zhang and Wenfeng Liu
Text sentiment analysis is an important but challenging task. Remarkable success has been achieved along with the wide application of deep learning methods, but deep learning methods dealing with text sentiment classification tasks cannot fully exploit s...
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Ye Ma, Qing Chang, Huanzhang Lu and Junliang Liu
Recurrent neural networks (RNNs) remain challenging, and there is still a lack of long-term memory or learning ability in sequential data classification and prediction. In this paper, we propose a flexible recurrent model, BIdirectional COnvolutional RaN...
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Alvaro A. Teran-Quezada, Victor Lopez-Cabrera, Jose Carlos Rangel and Javier E. Sanchez-Galan
Convolutional neural networks (CNN) have provided great advances for the task of sign language recognition (SLR). However, recurrent neural networks (RNN) in the form of long?short-term memory (LSTM) have become a means for providing solutions to problem...
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Yunpiao Cai, Weixing Qian, Jiaqi Zhao, Jiayi Dong and Tianxiao Shen
In this paper, we propose a novel visual?inertial simultaneous localization and mapping (SLAM) method for intelligent navigation systems that aims to overcome the challenges posed by dynamic or large-scale outdoor environments. Our approach constructs a ...
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Sergi Mas-Pujol, Esther Salamí and Enric Pastor
Meeting the demand with the available airspace capacity is one of the most challenging problems faced by Air Traffic Management. Nowadays, this collaborative Demand?Capacity Balancing process often ends up enforcing Air Traffic Flow Management regulation...
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Furkan Kayim,Atinç Yilmaz
Pág. 16 - 24
In ancient times, trade was carried out by barter. With the use of money and similar means, the concept of financial instruments emerged. Financial instruments are tools and documents used in the economy. Financial instruments can be foreign exchange rat...
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Imtiaz Ullah, Ayaz Ullah and Mazhar Sajjad
The tremendous number of Internet of Things (IoT) applications, with their ubiquity, has provided us with unprecedented productivity and simplified our daily life. At the same time, the insecurity of these technologies ensures that our daily lives are su...
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Lyudmyla Kirichenko, Tamara Radivilova, Bohdan Sydorenko and Sergiy Yakovlev
Shoplifting is a major problem for shop owners and many other parties, including the police. Video surveillance generates huge amounts of information that staff cannot process in real time. In this article, the problem of detecting shoplifting in video r...
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