|
|
|
|
|
Elie Azeraf, Emmanuel Monfrini and Wojciech Pieczynski
Practitioners have used hidden Markov models (HMMs) in different problems for about sixty years. Moreover, conditional random fields (CRFs) are an alternative to HMMs and appear in the literature as different and somewhat concurrent models. We propose tw...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wentao Wang, Xuan Ke and Lingxia Wang
A data center network is vulnerable to suffer from concealed low-rate distributed denial of service (L-DDoS) attacks because its data flow has the characteristics of data flow delay, diversity, and synchronization. Several studies have proposed addressin...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wentao Wang, Xuan Ke and Lingxia Wang
A data center network is vulnerable to suffer from concealed low-rate distributed denial of service (L-DDoS) attacks because its data flow has the characteristics of data flow delay, diversity, and synchronization. Several studies have proposed addressin...
ver más
|
|
|
|
|
|
|
|
|
|
|
Uttam Kumar, Kumar S. Raja, Chiranjit Mukhopadhyay and T.V. Ramachandra
Signals acquired by sensors in the real world are non-linear combinations, requiring non-linear mixture models to describe the resultant mixture spectra for the endmember?s (pure pixel?s) distribution. This communication discusses inferring class fractio...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nguyet Nguyen
Hidden Markov model (HMM) is a statistical signal prediction model, which has been widely used to predict economic regimes and stock prices. In this paper, we introduce the application of HMM in trading stocks (with S&P 500 index being an example) ba...
ver más
|
|
|
|
|
|
|
|
|
|
|
Joseph Ndong and Ted Soubdhan
Building a sophisticated forecasting framework for solar and photovoltaic power production in geographic zones with severe meteorological conditions is very challenging. This difficulty is linked to the high variability of the global solar radiation on w...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mahmoud Elmezain, Majed M. Alwateer, Rasha El-Agamy, Elsayed Atlam and Hani M. Ibrahim
Automatic key gesture detection and recognition are difficult tasks in Human?Computer Interaction due to the need to spot the start and the end points of the gesture of interest. By integrating Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs),...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lin Qu, Yue Zhou, Jiangxin Li, Qiong Yu and Xinguo Jiang
Map matching of trajectory data has wide applications in path planning, traffic flow analysis, and intelligent driving. The process of map matching involves matching GPS trajectory points to roads in a roadway network, thereby converting a trajectory seq...
ver más
|
|
|
|
|
|
|
|
|
|
|
Monika Tanwar, Hyunseok Park and Nagarajan Raghavan
Lubricating Oil Diagnostics and Prognostics.
|
|
|
|
|
|
|
|
|
|
|
Tian Xia and Xuemin Chen
Many machine learning methods have been applied for short messaging service (SMS) spam detection, including traditional methods such as naïve Bayes (NB), vector space model (VSM), and support vector machine (SVM), and novel methods such as long short-ter...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mladen Russo, Maja Stella, Marjan Sikora and Vesna Pekic
Accurate speech recognition can provide a natural interface for human?computer interaction. Recognition rates of the modern speech recognition systems are highly dependent on background noise levels and a choice of acoustic feature extraction method can ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Huan Wang, Bin Wu, Yuancheng Yao and Mingwei Qin
Spectrum sensing is the necessary premise for implementing cognitive radio technology. The conventional wideband spectrum sensing methods mainly work with sweeping frequency and still face major challenges in performance and efficiency. This paper introd...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alaa E. Abdel Hakim and Wael Deabes
In supervised Activities of Daily Living (ADL) recognition systems, annotating collected sensor readings is an essential, yet exhaustive, task. Readings are collected from activity-monitoring sensors in a 24/7 manner. The size of the produced dataset is ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jia-Hua Chen and Shu-Liang Zou
Shearing machines are the key pieces of equipment for spent–fuel reprocessing in commercial reactors. Once a failure happens and is not detected in time, serious consequences will arise. It is very important to monitor the shearing machine and to d...
ver más
|
|
|
|
|
|
|
|
|
|
|
Nyothiri Aung, Weidong Zhang, Sahraoui Dhelim and Yibo Ai
With the emergence of autonomous vehicles and internet of vehicles (IoV), future roads of smart cities will have a combination of autonomous and automated vehicles with regular vehicles that require human operators. To ensure the safety of the road commu...
ver más
|
|
|
|
|
|
|
|
|
|
|
Stephen Winters-Hilt and Andrew J. Lewis
One of the main limitations of the typical hidden Markov model (HMM) implementation for gene structure identification is that a single structure is identified on a given sequence of genomic data?i.e., identification of overlapping structure is not direct...
ver más
|
|
|
|
|
|
|
|
|
|
|
Eva L. IGLESIAS,Lourdes BORRAJO,R. ROMERO
Pág. 21 - 34
|
|
|
|
|
|
|
|
|
|
|
Shengxian Tang, Hexu Liu, Manea Almatared, Osama Abudayyeh, Zhen Lei and Alvis Fong
Construction-oriented quantity take-off (QTO) refers to the process of determining the quantities for construction items or work packages in accordance with their descriptions. However, the current construction-oriented QTO practice relies on estimators?...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mohammed Saïd Kasttet, Abdelouahid Lyhyaoui, Douae Zbakh, Adil Aramja and Abderazzek Kachkari
Recently, artificial intelligence and data science have witnessed dramatic progress and rapid growth, especially Automatic Speech Recognition (ASR) technology based on Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). Consequently, new end-to-...
ver más
|
|
|
|
|
|
|
|
|
|
|
Juan M. Perero-Codosero, Fernando M. Espinoza-Cuadros and Luis A. Hernández-Gómez
This paper describes a comparison between hybrid and end-to-end Automatic Speech Recognition (ASR) systems, which were evaluated on the IberSpeech-RTVE 2020 Speech-to-Text Transcription Challenge. Deep Neural Networks (DNNs) are becoming the most promisi...
ver más
|
|
|
|
|
|