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Academic Articles & Research Papers
Showing 20 of 33 academic articles
Santanu Pattanayak • Apress eBooks
(2017)
Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with T...
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DOI: https://doi.org/10.1007/978-1-4842-3096-1
Georgiana Țucudean, Marian Bucos, Bogdan Drăgulescu, Cătălin Daniel Căleanu • PeerJ Computer Science
(2024)
Natural language processing (NLP) tasks can be addressed with several deep learning architectures, and many different approaches have proven to be efficient. This study aims to briefly summarize the use cases for NLP tasks along with the ma...
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DOI: https://doi.org/10.7717/peerj-cs.2222
PMC: 11322986
Guoyu Zuo, Minghui Zhang, Jingwei Ren, Qifei Wu et al. • CAAI Transactions on Intelligence Technology
(2026)
ABSTRACT Knee joint moment estimation is a critical component in biomechanical analysis, with profound implications for rehabilitation assessment and the development of assistive devices like exoskeletons. However, existing data‐driven appr...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/cit2.70165
V. G. Dhanya, Anakkallan Subeesh, Nand Lal Kushwaha, Dinesh Kumar Vishwakarma et al. • Artificial Intelligence in Agriculture
(2022)
The agriculture industry is undergoing a rapid digital transformation and is growing powerful by the pillars of cutting-edge approaches like artificial intelligence and allied technologies. At the core of artificial intelligence, deep learn...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.aiia.2022.09.007
Arailym Serikbay, Venera Nurmanova, Yerbol Akhmetov, Amin Zollanvari et al. • International Transactions on Electrical Energy Systems
(2025)
Regular monitoring of outdoor insulators is crucial to ensure the reliable functioning of the power grid. With recent progress in computer vision technologies, traditional manual and expensive visual inspections can now be replaced by autom...
DOAJ
Open Access (DOAJ)
DOI: 10.1155/etep/8669289
Eirini Cholopoulou, Dimitrios E. Diamantis, Dimitra-Christina C. Koutsiou, Dimitris K. Iakovidis • IEEE Access
(2026)
Effective shadow removal is pivotal in enhancing visual image quality in applications such as computer vision and digital photography. During the last decades physics-based and machine learning methodologies have been proposed; however, mos...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2026.3728048
Jin Liu, Yi Feng Pan, Min Li, Ziyue Chen et al. • Big Data Mining and Analytics
(2018)
Deep learning provides exciting solutions in many fields, such as image analysis, natural language processing, and expert system, and is seen as a key method for various future applications. On account of its non-invasive and good soft tiss...
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DOI: https://doi.org/10.26599/bdma.2018.9020001
Mohammad Mustafa Taye • Computers
(2023)
In recent years, deep learning (DL) has been the most popular computational approach in the field of machine learning (ML), achieving exceptional results on a variety of complex cognitive tasks, matching or even surpassing human performance...
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DOI: https://doi.org/10.3390/computers12050091
Priya Mathur, Dheeraj Kumar, Farhan Sheth, Hammad Shaikh et al. • Scientific Reports
(2025)
Abstract Accurately predicting the specific heat capacity of nanofluids is critical for optimizing their performance in engineering and industrial applications. This study explores twelve machine learning and deep learning models using conv...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-28268-z
Fatima Rauf, Muhammad Attique Khan, Ali Kashif Bashir, Kiran Jabeen et al. • Frontiers in Medicine
(2023)
Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves ...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fmed.2023.1330218
Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, Kiana Jafari Meimandi et al. • International Conference on Machine Learning and Applications
(2017)
Increasingly large document collections require improved information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which has become an importan...
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Open Access
DOI: https://doi.org/10.1109/icmla.2017.0-134
Ammar Mohammed, Rania Kora • Journal of King Saud University - Computer and Information Sciences
(2023)
In machine learning, two approaches outperform traditional algorithms: ensemble learning and deep learning. The former refers to methods that integrate multiple base models in the same framework to obtain a stronger model that outperforms t...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.jksuci.2023.01.014
Boris Pyakillya, Н. Я. Казаченко, N Mikhailovsky • Journal of Physics Conference Series
(2017)
The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG d...
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DOI: https://doi.org/10.1088/1742-6596/913/1/012004
Daniel W. Otter, Julian Richard Medina, Jugal Kumar Kalita • IEEE Transactions on Neural Networks and Learning Systems
(2020)
Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This article provides a brief introduction to the field and a quick overview of deep learni...
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Open Access
DOI: https://doi.org/10.1109/tnnls.2020.2979670
Zhonghua Feng, Minglun Ren • Applied Sciences
(2026)
Rotating machinery prognostics is essential for ensuring the reliability and operational safety of industrial systems. Although gated recurrent units (GRUs) have achieved competitive performance in remaining useful life (RUL) prediction, wh...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app16178379
Yotsawat Pomyen, Kwanjeera Wanichthanarak, Patcha Poungsombat, Johannes Francois Fahrmann et al. • Computational and Structural Biotechnology Journal
(2020)
In the past few years, deep learning has been successfully applied to various omics data. However, the applications of deep learning in metabolomics are still relatively low compared to others omics. Currently, data pre-processing using con...
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DOI: https://doi.org/10.1016/j.csbj.2020.09.033
PMC: 7575644
Luke de Oliveira • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
(2022)
Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...
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DOI: https://doi.org/10.1007/jhep07%282016%29069
Luke de Oliveira, Michael Kagan, Lester W. Mackey, Benjamin Philip Nachman et al. • Journal of High Energy Physics
(2016)
Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...
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DOI: https://doi.org/10.1007/jhep07(2016)069
Alexander Craik, Yongtian He, Jose Luis Contreras-Vidal • Journal of Neural Engineering
(2019)
OBJECTIVE: Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain-computer interfaces, BCI's), and even commercial applications. Many of the analyti...
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DOI: https://doi.org/10.1088/1741-2552/ab0ab5
Imma Lory Aprea, Gianni Bosi, Gabriele Sbaiz, Salvatore Scognamiglio • Mathematics
(2025)
In this paper, we tackle a bi-objective optimization problem in which we aim to maximize the portfolio diversification and, at the same time, minimize the portfolio volatility, where the ESG (Environmental, Social, and Governance) informati...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/math13203308