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Ana Corceiro, Nuno Pereira, Khadijeh Alibabaei and Pedro D. Gaspar
The global population?s rapid growth necessitates a 70% increase in agricultural production, posing challenges exacerbated by weed infestation and herbicide drawbacks. To address this, machine learning (ML) models, particularly convolutional neural netwo...
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Kiriakos Alexiou, Efthimios G. Pariotis, Theodoros C. Zannis and Helen C. Leligou
The maritime industry is one of the most competitive industries today. However, there is a tendency for the profit margins of shipping companies to reduce due to an increase in operational costs, and it does not seem that this trend will change in the ne...
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T.A. Osipova,K.S. Zaytsev,V.O. Bifert
Pág. 23 - 29
Today there is a significant increase in the number of incidents involving the use of plastic cards, as well as a variety of fraudulent methods used by cybercriminals. The presented article is devoted to the application of machine learning methods to cou...
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T.A. Osipova,K.S. Zaytsev,V.O. Bifert
Pág. 23 - 29
Today there is a significant increase in the number of incidents involving the use of plastic cards, as well as a variety of fraudulent methods used by cybercriminals. The presented article is devoted to the application of machine learning methods to cou...
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Armin Rashidi Nasab and Hazem Elzarka
The deterioration of a bridge?s deck endangers its safety and serviceability. Ohio has approximately 45,000 bridges that need to be monitored to ensure their structural integrity. Adequate prediction of the deterioration of bridges at an early stage is c...
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Elias S. Leggesse, Fasikaw A. Zimale, Dagnenet Sultan, Temesgen Enku, Raghavan Srinivasan and Seifu A. Tilahun
Water quality degradation of freshwater bodies is a concern worldwide, particularly in Africa, where data are scarce and standard water quality monitoring is expensive. This study explored the use of remote sensing imagery and machine learning (ML) algor...
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Moshe Sipper
Hyperparameters in machine learning (ML) have received a fair amount of attention, and hyperparameter tuning has come to be regarded as an important step in the ML pipeline. However, just how useful is said tuning? While smaller-scale experiments have be...
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Vineet Chaturvedi and Walter T. de Vries
Urbanization is persistent globally and has increasingly significant spatial and environmental consequences. It is especially challenging in developing countries due to the increasing pressure on the limited resources, and damage to the bio-physical envi...
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Dthenifer Cordeiro Santana, Gustavo de Faria Theodoro, Ricardo Gava, João Lucas Gouveia de Oliveira, Larissa Pereira Ribeiro Teodoro, Izabela Cristina de Oliveira, Fábio Henrique Rojo Baio, Carlos Antonio da Silva Junior, Job Teixeira de Oliveira and Paulo Eduardo Teodoro
Using multispectral sensors attached to unmanned aerial vehicles (UAVs) can assist in the collection of morphological and physiological information from several crops. This approach, also known as high-throughput phenotyping, combined with data processin...
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Flavo Elano Soares de Souza and José Inácio de Jesus Rodrigues
With the growing availability of remote sensing orbital spatial data, the applications of machine learning (ML) algorithms have been leveraging the field of process automation in image classification. The present work aimed to evaluate the precision and ...
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Javier Alberto Pérez-Castán, Luis Pérez-Sanz, Lidia Serrano-Mira, Francisco Javier Saéz-Hernando, Irene Rodríguez Gauxachs and Víctor Fernando Gómez-Comendador
Given the ongoing interest in the application of Machine Learning (ML) techniques, the development of new Air Traffic Control (ATC) tools is paramount for the improvement of the management of the air transport system. This article develops an ATC tool ba...
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Amani Aldahiri, Bashair Alrashed and Walayat Hussain
Machine learning (ML) is a powerful tool that delivers insights hidden in Internet of Things (IoT) data. These hybrid technologies work smartly to improve the decision-making process in different areas such as education, security, business, and the healt...
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Subramanyam Shashi Kumar and Prakash Ramachandran
Nowadays, healthcare is becoming very modern, and the support of Internet of Things (IoT) is inevitable in a personal healthcare system. A typical personal healthcare system acquires vital parameters from human users and stores them in a cloud platform f...
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Ayele Tesema Chala and Richard Ray
Conventional soil classification methods are expensive and demand extensive field and laboratory work. This research evaluates the efficiency of various machine learning (ML) algorithms in classifying soils based on Robertson?s soil behavioral types. Thi...
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Mohammed A. Mohammed, Manel Boujelben and Mohamed Abid
Recently, the advent of blockchain (BC) has sparked a digital revolution in different fields, such as finance, healthcare, and supply chain. It is used by smart healthcare systems to provide transparency and control for personal medical records. However,...
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Manisha Sanjay Sirsat, Paula Rodrigues Oblessuc and Ricardo S. Ramiro
Genomic Prediction (GP) is a powerful approach for inferring complex phenotypes from genetic markers. GP is critical for improving grain yield, particularly for staple crops such as wheat and rice, which are crucial to feeding the world. While machine le...
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Usman Ali, Travis J. Esau, Aitazaz A. Farooque, Qamar U. Zaman, Farhat Abbas and Mathieu F. Bilodeau
Land use and land cover (LULC) classification maps help understand the state and trends of agricultural production and provide insights for applications in environmental monitoring. One of the major downfalls of the LULC technique is inherently linked to...
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Polina Simkina
The Compact Muon Solenoid (CMS) is one of the general purpose detectors at the CERN Large Hadron Collider (LHC), where the products of proton?proton collisions at the center of mass energy up to 13.6 TeV are reconstructed. The electromagnetic calorimeter...
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Cutifa Safitri, Yoshihide Yamada, Sabariah Baharun, Shidrokh Goudarzi, Quang Ngoc Nguyen, Keping Yu and Takuro Sato
This research proposes an intelligent classification framework for quality of service (QoS) performance improvement in information-centric networking (ICN). The proposal works towards keyword classification techniques to obtain the most valuable informat...
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Cutifa Safitri, Yoshihide Yamada, Sabariah Baharun, Shidrokh Goudarzi, Quang Ngoc Nguyen, Keping Yu and Takuro Sato
This research proposes an intelligent classification framework for quality of service (QoS) performance improvement in information-centric networking (ICN). The proposal works towards keyword classification techniques to obtain the most valuable informat...
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