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Roberto Corizzo and Sebastian Leal-Arenas
Detection of AI-generated content is a crucially important task considering the increasing attention towards AI tools, such as ChatGPT, and the raised concerns with regard to academic integrity. Existing text classification approaches, including neural-n...
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Anastasia Fedotova, Aleksandr Romanov, Anna Kurtukova and Alexander Shelupanov
This article is the third paper in a series aimed at the establishment of the authorship of Russian-language texts. This paper considers methods for determining the authorship of classical Russian literary texts, as well as fanfiction texts. The process ...
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Paolo Massimo Buscema, Giulia Massini, Giovanbattista Raimondi, Giuseppe Caporaso, Marco Breda and Riccardo Petritoli
The automatic identification system (AIS) facilitates the monitoring of ship movements and provides essential input parameters for traffic safety. Previous studies have employed AIS data to detect behavioral anomalies and classify vessel types using supe...
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Luca Scrucca
Imbalanced data present a pervasive challenge in many real-world applications of statistical and machine learning, where the instances of one class significantly outnumber those of the other. This paper examines the impact of class imbalance on the perfo...
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Javad Hassannataj Joloudari, Abdolreza Marefat, Mohammad Ali Nematollahi, Solomon Sunday Oyelere and Sadiq Hussain
Imbalanced Data (ID) is a problem that deters Machine Learning (ML) models from achieving satisfactory results. ID is the occurrence of a situation where the quantity of the samples belonging to one class outnumbers that of the other by a wide margin, ma...
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Tingkai Hu, Zuqin Chen, Jike Ge, Zhaoxu Yang and Jichao Xu
Insufficiently labeled samples and low-generalization performance have become significant natural language processing problems, drawing significant concern for few-shot text classification (FSTC). Advances in prompt learning have significantly improved t...
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Yiliang Wan, Yuwen Fei, Rui Jin, Tao Wu and Xinguang He
The effective extraction of impervious surfaces is critical to monitor their expansion and ensure the sustainable development of cities. Open geographic data can provide a large number of training samples for machine learning methods based on remote-sens...
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Khaled A. Alaghbari, Heng-Siong Lim, Mohamad Hanif Md Saad and Yik Seng Yong
The intrusion detection system (IDS) is a promising technology for ensuring security against cyber-attacks in internet-of-things networks. In conventional IDS, anomaly detection and feature extraction are performed by two different models. In this paper,...
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Diogo Ribeiro, Luís Miguel Matos, Guilherme Moreira, André Pilastri and Paulo Cortez
Within the context of Industry 4.0, quality assessment procedures using data-driven techniques are becoming more critical due to the generation of massive amounts of production data. In this paper, we address the detection of abnormal screw tightening pr...
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Vladimir Estivill-Castro, Eugene Gilmore and René Hexel
Interactive machine learning (IML) enables the incorporation of human expertise because the human participates in the construction of the learned model. Moreover, with human-in-the-loop machine learning (HITL-ML), the human experts drive the learning, an...
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