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Academic Articles & Research Papers
Showing 20 of 872 academic articles
Hui Fang, Guisheng Liao, Yongjun Liu, Cao Zeng et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2024)
Video synthetic aperture radar (video SAR) has been successfully applied in many fields and the registration of the video SAR images has been proven to be a crucial step in their preprocessing. However, video SAR images exhibit more severe ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2024.3465835
Kyosuke Nagura, Satoko Watanabe, Taro Watanabe, Taro Watanabe et al. • Frontiers in Pharmacology
(2026)
IntroductionOveractive bladder (OAB) drugs are widely prescribed, yet the occurrence of atrial fibrillation (AF) after treatment initiation remains poorly characterized.MethodsWe evaluated reports of AF associated with OAB medications using...
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Open Access (DOAJ)
DOI: 10.3389/fphar.2025.1700587
Nasrin Rezaei, Andreas Rehkopf • Advances in Engineering and Intelligence Systems
(2026)
In the context of big data, data preprocessing, especially data whitening, plays a pivotal role in improving the effectiveness of AI models. While traditional whitening methods suffer from severe computational bottlenecks, arising from the ...
DOAJ
Open Access (DOAJ)
DOI: 10.22034/aeis.2026.575941.1510
Valery Dmitrievich Solovyev, Marina Ivanovna Solnyshkina, Danielle S. McNamara • Russian Journal of Linguistics
(2022)
The dramatic expansion of modern linguistic research and enhanced accuracy of linguistic analysis have become a reality due to the ability of artificial neural networks not only to learn and adapt, but also carry out automate linguistic ana...
DOAJ
Open Access (DOAJ)
DOI: 10.22363/2687-0088-31326
Kai-Wei Chang, Vinod M. Prabhakaran, Vicente Ordóñez • Conference on Empirical Methods in Natural Language Processing (EMNLP)
(2019)
Recent advances in data-driven machine learning techniques (e.g., deep neural networks) have revolutionized many natural language processing applications. These approaches automatically learn how to make decisions based on the statistics an...
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Wei Wang, Jianxun Gang • IEEE International Conference on Information Systems and Computer Aided Education (ICISCAE)
(2018)
Convolutional neural network (Convolutionl Neural Network, CNN) is a multiple-layer neural network method to learn hierarchical characteristic of data. In recent years, CNN has developed rapidly in the design and calculation of natural lang...
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DOI: https://doi.org/10.1109/iciscae.2018.8666928
Jianye Xie, Yulan Zhang, Huaizhen Kou, Xiaoran Zhao et al. • Tsinghua Science and Technology
(2025)
Event extraction is an important part of natural language information extraction, and it’s widely employed in other natural language processing tasks including question answering and machine reading comprehension. However, there is a lack o...
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Open Access (DOAJ)
DOI: 10.26599/TST.2023.9010139
Zhewei Zhang, Huzi Cheng, Tianming Yang • PLoS Computational Biology
(2020)
The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. Th...
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Open Access (DOAJ)
DOI: 10.1371/journal.pcbi.1008342
Aditya Malte, Pratik Ratadiya • arXiv (Cornell University)
(2019)
In this paper, we present a study of the recent advancements which have helped bring Transfer Learning to NLP through the use of semi-supervised training. We discuss cutting-edge methods and architectures such as BERT, GPT, ELMo, ULMFit amo...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1910.07370
Jonas Rieger, Kostiantyn Yanchenko, Mattes Ruckdeschel, Gerret von Nordheim et al. • Studies in Communication, Media
(2024)
Pre-trained language models (PLM) based on transformer neural networks developed in the field of natural language processing (NLP) offer great opportunities to improve automatic content analysis in communication science, especially for the ...
DOAJ
Open Access (DOAJ)
DOI: 10.5771/2192-4007-2024-1-72
Dheya Mustafa, Safaa M. Khabour, Mousa Al-kfairy, Ahmed Shatnawi • PeerJ Computer Science
(2025)
Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a cru...
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Open Access (DOAJ)
DOI: 10.7717/peerj-cs.2669
Arezo Shakeri, Mina Farmanbar • Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring
(2025)
Abstract INTRODUCTION Alzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD. M...
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Open Access (DOAJ)
DOI: 10.1002/dad2.70082
Albert Ntumba Nkongolo, Yae Olatoundji Gaba, Kafunda Katalay Pierre, Esther Matendo Mabela et al. • Journal of Innovation Information Technology and Application
(2025)
This study explores the application of natural language processing (NLP) techniques in financial time series forecasting, specifically in predicting stock prices. Historical stock price data and textual data from financial news articles and...
DOAJ
Open Access (DOAJ)
DOI: 10.35970/jinita.v7i1.2290
Shima Javanmardi, Ali Mohammad Latif, Mohammad Taghi Sadeghi, Mehrdad Jahanbanifard et al. • Sensors
(2022)
In image captioning models, the main challenge in describing an image is identifying all the objects by precisely considering the relationships between the objects and producing various captions. Over the past few years, many methods have b...
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Open Access (DOAJ)
DOI: 10.3390/s22218376
Simov Kiril, Osenova Petya • Cybernetics and Information Technologies
(2018)
With the availability of large language data online, cross-linked lexical resources (such as BabelNet, Predicate Matrix and UBY) and semantically annotated corpora (SemCor, OntoNotes, etc.), more and more applications in Natural Language Pr...
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Open Access (DOAJ)
DOI: 10.2478/cait-2018-0008
Ivan S. Blekanov, Nikita Tarasov, Svetlana S. Bodrunova • Future Internet
(2022)
Abstractive summarization is a technique that allows for extracting condensed meanings from long texts, with a variety of potential practical applications. Nonetheless, today’s abstractive summarization research is limited to testing the mo...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/fi14030069
Wenpeng Yin, Katharina Kann, Mo Yu, Hinrich Schütze • arXiv (Cornell University)
(2017)
Deep neural networks (DNN) have revolutionized the field of natural language processing (NLP). Convolutional neural network (CNN) and recurrent neural network (RNN), the two main types of DNN architectures, are widely explored to handle var...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1702.01923
Yasha Hasija, Rajkumar Chakraborty • CRC Press eBooks
(2021)
Natural language processing is a fast-evolving field with popular applications in language translation, speech recognition, text classification, and summarization of text, among others. The central aspect of NLP is vectorizing text data. Te...
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DOI: https://doi.org/10.1201/9781003090113-15-15
Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi, Chenliang Li • ACM Transactions on Intelligent Systems and Technology
(2020)
With the development of high computational devices, deep neural networks (DNNs), in recent years, have gained significant popularity in many Artificial Intelligence (AI) applications. However, previous efforts have shown that DNNs are vulne...
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Open Access
DOI: https://doi.org/10.1145/3374217
Yue Zhang, Zhiyang Teng • Cambridge University Press eBooks
(2020)
With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are sy...
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DOI: https://doi.org/10.1017/9781108332873