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Browsing Articole din publicaţii internaţionale by Subject "machine learning"

Browsing Articole din publicaţii internaţionale by Subject "machine learning"

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  • Assessing the relationship between landslide susceptibility and land cover change using machine learning 
    NGUYEN, Huu Duy; VU, Tung Cong; BRETCAN, Petre; PETRISOR, Alexandru-Ionut (Publishing House of Natural Science and Technology, VAST, 2024)
    Landslides are natural disasters most frequent in the mountain region of Vietnam, producing critical damage to human lives and assets. Therefore, precisely identifying the landslide occurrence probability within the region ...
  • Augmentation of wastewater-based epidemiology with machine learning to support global health surveillance 
    AßMANN, Eva; GREINER, Timo; RICHARD, Hugues; WADE, Matthew; AGRAWAL, Shelesh; AMMAN, Fabian; BÖTTCHER, Sindy; LACKNER, Susanne; LANDTHALER, Markus; MANGUL, Serghei; MUNTEANU, Viorel; PSOMOPOULOS, Fotis; SMITH, Maureen; TROFIMOVA, Maria; ULLRICH, Alexander; KLEIST, Max Von; WYLER, Emanuel; HÖLZER, Martin; IRRGANG, Christopher (Springer Nature, 2025)
    Wastewater-based epidemiology (WBE) has proven to be a valuable tool for monitoring the evolution and spread of global health threats, from pathogens to antimicrobial resistances. Throughout the COVID-19 pandemic, multiple ...
  • Automatic Detection of Arabicized Berber and Arabic Varieties 
    ADOUANE, Wafia; SEMMAR, Nasredine; JOHANSSON, Richard; BOBICEV, Victoria (The COLING 2016 Organizing Committee, 2016)
    Automatic Language Identification (ALI) is the detection of the natural language of an input text by a machine. It is the first necessary step to do any language-dependent natural language processing task. Various methods ...
  • Banana Reigns Wilt based on machine learning and UAV-Based multispectral imagery 
    NGUYEN, Quoc-Huy; DU, Quan Vu Viet; PHAM, Viet Thanh; VUONG, Hong Nhat; NGUYEN, Van Hong; SANG, Tran Van; PETRIŞOR, Alexandru-Ionuţ (Asociatia Geographia Technica, 2025)
    Reigns Wilt disease is one of the diseases that cause serious damage to crops in tropical monsoon regions. Among them, banana wilt disease is one of the common and worrying problems, especially in Vietnam. Therefore, ...
  • Classification of Emotion Words in Russian and Romanian Languages 
    SOKOLOVA, Marina; BOBICEV, Victoria (Association for Computational Linguistics, 2009)
    This paper presents a machine learning study of affective words in Russian and Romanian languages. We tag the word affective meaning by one of the WordNet Affect six labels anger, disgust, fear, joy, sadness, surprise and ...
  • An Effective and Robust Method for Short Text Classification 
    BOBICEV, Victoria; SOKOLOVA, Marina (The AAAI Press, Menlo Park, California, 2008)
    Classification of texts potentially containing a complex and specific terminology requires the use of learning methods that do not rely on extensive feature engineering. In this work we use prediction by partial matching ...
  • Estimation of Kolmogorov-Chaitin complexity on continuous biomedical data for machine learning purposes 
    IAPASCURTA, Victor (Springer Nature, 2024)
    In the field of scientific research, the quest for understanding and explaining complex phenomena often involves uncovering patterns and underlying structures. To achieve this, researchers employ various methodologies and ...
  • A framework for flood depth using hydrodynamic modeling and machine learning in the coastal province of Vietnam 
    NGUYEN, Huu Duy; DANG, Dinh Kha; NGUYEN, Y Nhu; VAN, Chien Pham; TRUONG, Quang-Hai; BUI, Quang-Thanh; PETRISOR, Alexandru-Ionut (Publishing House of Natural Science and Technology, VAST, 2023)
    Flood models based on traditional hydrodynamic modeling encounter significant difficulties with real-time predictions, require enormous computational resources, and perform poorly in data-limited regions. The difficulties ...
  • Hardware implementation of Hopfield-like neural networks: Quantitative analysis of FPGA approach 
    ZAPOROJAN, Sergiu; CARBUNE, Viorel; SLAVESCU, Radu Razvan (IEEE, 2021)
    This paper provides a rigorous analysis of FPGA implementation of Hopfield-like neural networks. The relationship between the hardware resources used to synthesize the data path and those used to provide network connections ...
  • Integrated machine learning and remote sensing for groundwater potential mapping in the Mekong Delta in Vietnam 
    NGUYEN, Huu Duy; NGUYEN, Quoc-Huy; DANG, Dinh Kha; NGUYEN, Tien Giang; TRUONG, Quang Hai; NGUYEN, Van Hong; BRETCAN, Petre; ȘERBAN, Gheorghe; BUI, Quang-Thanh; PETRISOR, Alexandru-Ionut (Springer Nature, 2024)
    Evaluating groundwater potential is critical for the socioeconomic development of Vietnam. This research aims to assess the underground water potential in the country’s Mekong Delta using the machine learning (ML) such as ...
  • Intelligent condition monitoring of wind turbine blades: a preliminary approach 
    MUNTEANU, Eugeniu; ZAPOROJAN, Sergiu; DULGHERU, Valeriu; SLAVESCU, Radu Razvan; LARIN, Vladimir; RABEI, Ivan (Institute of Electrical and Electronics Engineers, 2022)
    Exploring new areas for wind energy production brings new challenges for improvement of wind farms, making them more reliable and suitable for increasing of the power grids. In this regard, it is important to study and ...
  • Language-independent features for authorship attribution on Ukrainian texts 
    HLAVCHEVA, Yuliia; GLAVCHEV, Maksym; BOBICEV, Victoria; KANISHCHEVA, Olga (Taras Shevchenko National University of Kyiv, 2021)
    Authorship attribution is the natural language processing task of the author identification of an input text. The main goal of this task is to define the salient characteristics of documents that capture the author's writing ...
  • Maximizing a neural network's accuracy and boosting the learning process for detecting the absolute colour similarity based on the centroids of normal distributions 
    SCROB, Sergiu; LISNIC, Inga; LEAHU, Alexei (Universitatea de Stat din Moldova, 2021)
    Our aim is to demonstrate that the ANN is prone to converge faster and with a higher level of accuracy using training data where tuples of triplets also represents the centroids of those 12 colour classes, considering each ...
  • A novel flood risk management approach based on future climate and land use change scenarios 
    NGUYEN, Huu Duy; NGUYEN, Quoc-Huy; DANG, Dinh Kha; VAN, Chien Pham; TRUONG, Quang Hai; PHAM, Si Dung; BUI, Quang-Thanh; PETRISOR, Alexandru-Ionut (Elsevier, 2024)
    This study aimed to develop a new approach by combining machine learning (namely the XGBoost, CatBoost, LightGBM, and ExtraTree models) and hydraulic modeling to predict the effects of climate change and LULC change on ...
  • What Goes Around Comes Around: Learning Sentiments in Online Medical Forums 
    BOBICEV, Victoria; SOKOLOVA, Marina; OAKES, Michael (Springer Nature Switzerland, 2015)
    It has been shown that online health-related discussions significantly influence the attitudes and behavioral intentions of the discussion participants. Although empirical evidence strongly supports the importance of ...

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