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Jiarui Xia and Yongshou Dai
Ground roll noise suppression is a crucial step in processing deep pre-stack seismic data. Recently, supervised deep learning methods have gained popularity in this field due to their ability to adaptively learn and extract powerful features. However, th...
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Xiaojuan Wang and Weilan Wang
As there is a lack of public mark samples of Tibetan historical document image characters at present, this paper proposes an unsupervised Tibetan historical document character recognition method based on deep learning (UD-CNN). Firstly, using the Tibetan...
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Hellena Hempe, Alexander Bigalke and Mattias Paul Heinrich
Background: Degenerative spinal pathologies are highly prevalent among the elderly population. Timely diagnosis of osteoporotic fractures and other degenerative deformities enables proactive measures to mitigate the risk of severe back pain and disabilit...
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Baris Yigin and Metin Celik
In recent years, advanced methods and smart solutions have been investigated for the safe, secure, and environmentally friendly operation of ships. Since data acquisition capabilities have improved, data processing has become of great importance for ship...
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Samuel-Soma M. Ajibade, Festus Victor Bekun, Festus Fatai Adedoyin, Bright Akwasi Gyamfi and Anthonia Oluwatosin Adediran
This study examines the research climate on machine learning applications in renewable energy (MLARE). Therefore, the publication trends (PT) and bibliometric analysis (BA) on MLARE research published and indexed in the Elsevier Scopus database between 2...
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María J. Verdú, Luisa M. Regueras, Juan P. de Castro and Elena Verdú
Learning Management Systems provide teachers with many functionalities to offer materials to students, interact with them and manage their courses. Recognizing teachers? instructing styles from their course designs would allow recommendations and best pr...
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Weijie Zhang, Lanping Zhang, Xixi Zhang, Yu Wang, Pengfei Liu and Guan Gui
Network traffic classification (NTC) has attracted great attention in many applications such as secure communications, intrusion detection systems. The existing NTC methods based on supervised learning rely on sufficient labeled datasets in the training ...
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Abrar Alamr and Abdelmonim Artoli
Anomaly detection is one of the basic issues in data processing that addresses different problems in healthcare sensory data. Technology has made it easier to collect large and highly variant time series data; however, complex predictive analysis models ...
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Dominik Stallmann and Barbara Hammer
Novel neural network models that can handle complex tasks with fewer examples than before are being developed for a wide range of applications. In some fields, even the creation of a few labels is a laborious task and impractical, especially for data tha...
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Thomas Di Martino, Bertrand Le Saux, Régis Guinvarc?h, Laetitia Thirion-Lefevre and Elise Colin
With an increase in the amount of natural disasters, the combined use of cloud-penetrating Synthetic Aperture Radar and deep learning becomes unavoidable for their monitoring. This article proposes a methodology for forest fire detection using unsupervis...
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