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Gabriel Dahia and Maurício Pamplona Segundo
We propose a method that can perform one-class classification given only a small number of examples from the target class and none from the others. We formulate the learning of meaningful features for one-class classification as a meta-learning problem i...
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Zida Ziyan Azkiya,Fatma Indriani,Heru Kartika Chandra
Pág. 129 - 133
Abstrak? Pada kasus deteksi penderita penyakit demam berdarah (Dengue Hemorrhagic Fever- DHF), data training yang tersedia umumnya hanya data pasien penderita positif. Sedangkan data orang normal (data negatif) tidak tersedia secara khusus. Pada makalah ...
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Loai Abdallah, Murad Badarna, Waleed Khalifa and Malik Yousef
In the computational biology community there are many biological cases that are considered as multi-one-class classification problems. Examples include the classification of multiple tumor types, protein fold recognition and the molecular classification ...
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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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Wen Xu, Julian Jang-Jaccard, Tong Liu, Fariza Sabrina and Jin Kwak
Existing generative adversarial networks (GANs), primarily used for creating fake image samples from natural images, demand a strong dependence (i.e., the training strategy of the generators and the discriminators require to be in sync) for the generator...
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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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Shuai Dong, Zhihua Yang, Wensheng Li and Kun Zou
Conveyors are used commonly in industrial production lines and automated sorting systems. Many applications require fast, reliable, and dynamic detection and recognition for the objects on conveyors. Aiming at this goal, we design a framework that involv...
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Jesús Alejandro Navarro-Acosta, Irma D. García-Calvillo, Vanesa Avalos-Gaytán and Edgar O. Reséndiz-Flores
In this study, a system for faults detection using a combination of Support Vector Data Description (SVDD) with metaheuristic algorithms is presented. The presented approach is applied to a real industrial process where the set of measured faults is scar...
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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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Danilo Avola, Luigi Cinque, Angelo Di Mambro, Anxhelo Diko, Alessio Fagioli, Gian Luca Foresti, Marco Raoul Marini, Alessio Mecca and Daniele Pannone
In recent years, small-scale Unmanned Aerial Vehicles (UAVs) have been used in many video surveillance applications, such as vehicle tracking, border control, dangerous object detection, and many others. Anomaly detection can represent a prerequisite of ...
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Valeri G. Gitis and Alexander B. Derendyaev
In this paper, we suggest two machine learning methods for seismic hazard forecast. The first method is used for spatial forecasting of maximum possible earthquake magnitudes (Mmax" role="presentation">????????Mmax
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O. I. Tymoshkin
Pág. 216 - 218
The problem of confidence testing applying to the regular iterative circuits is considered. Total number of such circuits from one class is estimated.
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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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Thimo F. Schindler, Simon Schlicht and Klaus-Dieter Thoben
Within the integration and development of data-driven process models, the underlying process is digitally mapped in a model through sensory data acquisition and subsequent modelling. In this process, challenges of different types and degrees of severity ...
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Everton Jose Santana, Ricardo Petri Silva, Bruno Bogaz Zarpelão and Sylvio Barbon Junior
With data collected by Internet of Things sensors, deep learning (DL) models can forecast the generation capacity of photovoltaic (PV) power plants. This functionality is especially relevant for PV power operators and users as PV plants exhibit irregular...
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Andrew D. Schiff, Mark T. Warren
Based on actual events, this case is concerned with the practical and managerial challenges associated with analyzing, designing and implementing a Business Intelligence (BI) / Corporate Performance Management (CPM)information technology solution in a la...
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John J. Lucas, Stephanie Clute
This Human Resource Management case focuses on a potential violation of a companys Employee Assistance Program (EAP) and the appropriate procedure to address this issue. This case is based upon an actual event that occurred at a production plant of a For...
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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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Pawel Fic, Adam Czornik and Piotr Rosikowski
This article aims to present the real-world implementation of an anomaly detection system of a hydraulic power unit. Implementation involved the Internet of Things approach. A detailed description of the system architecture is provided. The complete path...
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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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