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Academic Articles & Research Papers
Showing 20 of 938 academic articles
Jaesu Han, Sun Yi, Sangseok Yu • Scientific Reports
(2025)
Abstract Many controllers have been developed to control the motors of electric vehicles, but in the case of hydrogen vehicles, more delicate control is required, because power is provided through hybridization with batteries. The use of de...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-97082-4
Swaraja K., Akshitha V., Pranav K., Vyshnavi B. et al. • E3S Web of Conferences
(2021)
Depth estimation is a computer vision technique that is critical for autonomous schemes for sensing their surroundings and predict their own condition. Traditional estimating approaches, such as structure from motion besides stereo vision s...
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Open Access (DOAJ)
DOI: 10.1051/e3sconf/202130901069
N. Kannaiya Raja, E. Laxmi Lydia, Thumpala Archana Acharya, K. Radhika et al. • IEEE Access
(2023)
In recent years, drones or Unmanned Aerial Vehicles (UAVs) got significant attention among researchers because of their extensive application in commercial applications, border surveillance, etc. As the conventional terrestrial communicatio...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3324068
Szu-Pyng Kao, Yung-Chen Chang, Feng-Liang Wang • Sensors
(2023)
Bridges are often at risk due to the effects of natural disasters, such as earthquakes and typhoons. Bridge inspection assessments normally focus on cracks. However, numerous concrete structures with cracked surfaces are highly elevated or ...
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Open Access (DOAJ)
DOI: 10.3390/s23052572
Siripen Pongpaichet, Boonyapat Sukosit, Chitchaya Duangtanawat, Jiramed Jamjongdamrongkit et al. • IEEE Access
(2024)
Crimes result in not only loss to individuals but also hinder national economic growth. While crime rates have been reported to decrease in developed countries, underdeveloped and developing nations still suffer from prevalent crimes, espec...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3363879
Michele Avanzo, Lise Wei, Joseph Stancanello, Martin Vallières et al. • Medical Physics
(2020)
Radiomics is an emerging area in quantitative image analysis that aims to relate large-scale extracted imaging information to clinical and biological endpoints. The development of quantitative imaging methods along with machine learning has...
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DOI: https://doi.org/10.1002/mp.13678
PMC: 8965689
Christopher D. Manning • Computational Linguistics
(2015)
Deep Learning waves have lapped at the shores of computational linguistics for several years now, but 2015 seems like the year when the full force of the tsunami hit the major Natural Language Processing (NLP) conferences. However, some pun...
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Open Access
DOI: https://doi.org/10.1162/coli_a_00239
Francis Quintal Lauzon • International Conference on Information Science, Signal Processing and their Applications (ISSPA)
(2012)
Deep learning allows automatically learning multiple levels of representations of the underlying distribution of the data to be modeled. In this work, a specific implementation called stacked denoising autoencoders is explored. We contribut...
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DOI: https://doi.org/10.1109/isspa.2012.6310529
Sai Sri Hemantha Konala, Srinivas Koppu • Frontiers in Medicine
(2026)
IntroductionKidney-related disorders are one of the global health concerns that require timely detection to prevent severe health complications. The use of computed tomography (CT) images for accurate classification of kidney diseases is im...
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Open Access (DOAJ)
DOI: 10.3389/fmed.2026.1893419
Qing Chen, Aihuang Guo, Yaodong Cui • Applied Sciences
(2024)
To achieve the anticipated performance of massive multiple input multiple output (MIMO) systems in wireless communication, it is imperative that the user equipment (UE) accurately feeds the channel state information (CSI) back to the base s...
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Open Access (DOAJ)
DOI: 10.3390/app14041356
Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht • Journal Of Big Data
(2021)
Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with the major motifs of Data Augme...
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DOI: https://doi.org/10.1186/s40537-021-00492-0
PMC: 8287113
Polina Mamoshina, Armando S. Vieira, Eugene Lane, Alex A. Zhavoronkov • Molecular Pharmaceutics
(2016)
Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this ...
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DOI: https://doi.org/10.1021/acs.molpharmaceut.5b00982
Justin M. Johnson, Taghi M. Khoshgoftaar • Journal Of Big Data
(2019)
The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective classification with imbalanced data is an important area of research, as high class imbalance is naturally inherent in...
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DOI: https://doi.org/10.1186/s40537-019-0192-5
Emanuele Aiello, Mirko Agarla, Diego Valsesia, Paolo Napoletano et al. • IEEE Access
(2024)
Large-scale self-supervised pretraining of deep learning models is known to be critical in several fields, such as language processing, where its has led to significant breakthroughs. Indeed, it is often more impactful than architectural de...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3396990
Esraa Khatab, Ahmed Onsy, Ahmed Abouelfarag • Sensors
(2022)
One of the primary tasks undertaken by autonomous vehicles (AVs) is object detection, which comes ahead of object tracking, trajectory estimation, and collision avoidance. Vulnerable road objects (e.g., pedestrians, cyclists, etc.) pose a g...
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Open Access (DOAJ)
DOI: 10.3390/s22041663
Gabriel de Sousa Meira, João Victor Ferreira Guedes, Edilson de Souza Bias • Drones
(2024)
The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has...
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Open Access (DOAJ)
DOI: 10.3390/drones8070341
Daniel Kirk, E.J. Kok, Michele Tufano, Bedir Teki̇nerdoğan et al. • Advances in Nutrition
(2022)
Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and ...
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DOI: https://doi.org/10.1093/advances/nmac103
PMC: 9776646
Max Mowbray, Thomas Savage, Chufan Wu, Ziqi Song et al. • Biochemical Engineering Journal
(2021)
The field of machine learning is comprised of techniques, which have proven powerful approaches to knowledge discovery and construction of ‘digital twins’ in the highly dimensional, nonlinear and stochastic domains common to biochemical eng...
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DOI: https://doi.org/10.1016/j.bej.2021.108054
Róbert Skapinyecz • Machine Learning and Knowledge Extraction
(2026)
The paper presents a novel large language model-based neighbourhood search method for production scheduling using discrete-event simulation (DES) as the modelling and evaluation engine. The combination of large language models (LLMs) and DE...
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Open Access (DOAJ)
DOI: 10.3390/make8090284
Meghna Chaudhary, Kristin Kosyluk, Sylvia Thomas, Tempestt Neal • Scientific Reports
(2023)
Abstract According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rate...
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Open Access (DOAJ)
DOI: 10.1038/s41598-023-37592-1