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Ayanabha Jana and Shridevi S. Krishnakumar
The proposed research deals with constructing a sign gesture recognition system to enable improved interaction between sign and non-sign users. With respect to this goal, five types of features are utilized?hand coordinates, convolutional features, convo...
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Zhao Zhang, Feng Feng and Tingting Huang
The size of datasets is growing exponentially as information technology advances, and it is becoming more and more crucial to provide efficient learning algorithms for neural networks to handle massive amounts of data. Due to their potential for handling...
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Omar Abdulkhaleq Aldabash and Mehmet Fatih Akay
An IDS (Intrusion Detection System) is essential for network security experts, as it allows one to identify and respond to abnormal traffic present in a network. An IDS can be utilized for evaluating the various types of malicious attacks. Hence, detecti...
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Tianwei Lan, Zhaofa Zeng, Liguo Han and Jingwen Zeng
The neural network denoising technique has achieved impressive results by being able to automatically learn the effective signal from the data without any assumptions. However, it has been found experimentally that the performance of the method using neu...
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Wenbo He, Xiaoqiang Zhang, Zhenyu Feng, Qiqi Leng, Bufeng Xu and Xinmin Li
Dynamic load identification plays an important role in the field of fault diagnosis and structural modification design for aircraft. In conventional dynamic load identification approaches, accurate structural modeling is usually needed, which is difficul...
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Pietros André Balbino dos Santos, Felipe Schwerz, Luiz Gonsaga de Carvalho, Victor Buono da Silva Baptista, Diego Bedin Marin, Gabriel Araújo e Silva Ferraz, Giuseppe Rossi, Leonardo Conti and Gianluca Bambi
Reference evapotranspiration (ET0) is one important agrometeorological parameter for hydrological studies and climate risk zoning. ET0 calculation by the FAO Penman?Monteith method requires several input data. However, the availability of climate data ha...
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Andrei Konstantinov, Lev Utkin and Vladimir Muliukha
A new random forest-based model for solving the Multiple Instance Learning problem under small tabular data, called the Soft Tree Ensemble Multiple Instance Learning, is proposed. A new type of soft decision trees is considered, which is similar to the w...
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Alexander Sboev, Roman Rybka, Dmitry Kunitsyn, Alexey Serenko, Vyacheslav Ilyin and Vadim Putrolaynen
In this paper, we demonstrate that fixed-weight layers generated from random distribution or logistic functions can effectively extract significant features from input data, resulting in high accuracy on a variety of tasks, including Fisher?s Iris, Wisco...
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Ke Wu, Zhicheng Jia and Qifeng Duan
Sunscald in kiwifruit, an environmental stress caused by solar radiation during the summer, reduces fruit quality and yields and causes economic losses. The efficient and timely detection of sunscald and similar diseases is a challenging task but helps t...
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Piotr Górniak
In the paper, the author deals with modeling the stochastic behavior of ordinary patch antennas in terms of the mean and standard deviation of their reflection coefficient |S11| under the geometrical uncertainty associated with their manufacturing proces...
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Ebrahem A. Algehyne, Muhammad Lawan Jibril, Naseh A. Algehainy, Osama Abdulaziz Alamri and Abdullah K. Alzahrani
Breast cancer is one of the common malignancies among females in Saudi Arabia and has also been ranked as the one most prevalent and the number two killer disease in the country. However, the clinical diagnosis process of any disease such as breast cance...
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Diogo E. Moreira da Silva, Eduardo J. Solteiro Pires, Arsénio Reis, Paulo B. de Moura Oliveira and João Barroso
In Portugal, the dropout rate of university courses is around 29%. Understanding the reasons behind such a high desertion rate can drastically improve the success of students and universities. This work applies existing data mining techniques to predict ...
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Peng Li, Conglin Jin, Gang Ma, Jie Yang and Liping Sun
Real-time monitoring of the mooring safety of floating structures is of great significance to their production operations. A deep learning model is proposed here, based on the long short-term memory (LSTM) artificial neural network. Firstly, the numerica...
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Saeed Iqbal, Adnan N. Qureshi, Amin Ullah, Jianqiang Li and Tariq Mahmood
Deep learning is an obvious method for the detection of disease, analyzing medical images and many researchers have looked into it. However, the performance of deep learning algorithms is frequently influenced by hyperparameter selection, the question of...
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Sichen Li, Mélissa Zacharias, Jochem Snuverink, Jaime Coello de Portugal, Fernando Perez-Cruz, Davide Reggiani and Andreas Adelmann
The beam interruptions (interlocks) of particle accelerators, despite being necessary safety measures, lead to abrupt operational changes and a substantial loss of beam time. A novel time series classification approach is applied to decrease beam time lo...
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Abner Hernandez, Sunhee Kim and Minhwa Chung
One of the first cues for many neurological disorders are impairments in speech. The traditional method of diagnosing speech disorders such as dysarthria involves a perceptual evaluation from a trained speech therapist. However, this approach is known to...
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Tuan Anh Pham, Hai-Bang Ly, Van Quan Tran, Loi Van Giap, Huong-Lan Thi Vu and Hong-Anh Thi Duong
Axial bearing capacity of piles is the most important parameter in pile foundation design. In this paper, artificial neural network (ANN) and random forest (RF) algorithms were utilized to predict the ultimate axial bearing capacity of driven piles. An u...
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Md Abul Ehsan Bhuiyan, Feifei Yang, Nishan Kumar Biswas, Saiful Haque Rahat and Tahneen Jahan Neelam
The Integrated Multisatellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) Level 3 estimates rainfall from passive microwave sensors onboard satellites that are associated with several uncertainty sources such as sensor calibration, retr...
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Ananta Man Singh Pradhan and Yun-Tae Kim
Landslides impact on human activities and socio-economic development, especially in mountainous areas. This study focuses on the comparison of the prediction capability of advanced machine learning techniques for the rainfall-induced shallow landslide su...
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Inkyu Choi, Soo Hyun Bae and Nam Soo Kim
Audio event detection (AED) is a task of recognizing the types of audio events in an audio stream and estimating their temporal positions. AED is typically based on fully supervised approaches, requiring strong labels including both the presence and temp...
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