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Academic Articles & Research Papers
Showing 20 of 22 academic articles
Okonogi Noriyuki, Hashimoto Takatuki, Ishida Masaya, Ohno Toshiki et al. • Radiation Oncology
(2012)
Abstract Background Proton-beam therapy (PBT) provides therapeutic advantages over conformal x-ray therapy in sparing organs at risk when treating esophageal cancer because of the fundamental physical dose distribution of the proton-beam. H...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/1748-717X-7-173
Wei Chen, Yu Liu, Weiping Wang, Erwin M. Bakker et al. • IEEE Transactions on Pattern Analysis and Machine Intelligence
(2022)
In recent years a vast amount of visual content has been generated and shared from many fields, such as social media platforms, medical imaging, and robotics. This abundance of content creation and sharing has introduced new challenges, par...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tpami.2022.3218591
Jefferson S. Costa, Angelo Lunardi, Alessio Iovine, Darlan Alexandria Fernandes et al. • IEEE Access
(2025)
Model predictive control (MPC) has emerged as a highly regarded control strategy in power electronics for renewable energy applications. While it minimizes tracking errors and control effort, a significant challenge is the lack of systemati...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3603336
Rosana Abdoune, Lydia Lazib, Farida Dahmani-Bouarab, Nada Mimouni • Inteligencia Artificial
(2024)
In this work, we present a disciplinary e-tutoring system that integrates ONTO-TDM, an ontology designed for teaching domain modeling, with advanced transformer technology. Our primary objective is to enhance semantic similarity tasks withi...
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Open Access (DOAJ)
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
Anton Vijeevaraj Ann Sinthusha, Eugene Y. A. Charles, Ruvan Weerasinghe • IEEE Access
(2025)
Machine Reading Comprehension (MRC) is a challenging task in Natural Language Processing (NLP), crucial for automated customer support, enabling chatbots and virtual assistants to accurately understand and respond to queries. It also enhanc...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3530949
Prottay Kumar Adhikary, Isha Motiyani, Gayatri Oke, Maithili Joshi et al. • Journal of Medical Internet Research
(2025)
Abstract
BackgroundThe quality and accessibility of menstrual health education (MHE) in low- and middle-income countries, including India, remain inadequate due to persistent challenges (eg, poverty, social stigma, and gender in...
DOAJ
Open Access (DOAJ)
DOI: 10.2196/71977
Mosima A. Masethe, Sunday O. Ojo, Hlaudi D. Masethe • Computers
(2025)
Meaning conflation deficiency (MCD) presents a continual obstacle in natural language processing (NLP), especially for low-resourced and morphologically complex languages, where polysemy and contextual ambiguity diminish model precision in ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/computers14090402
裕二 池谷, Robert Tinn, Hao Cheng, MICHAEL A. LUCAS et al. • ACM Transactions on Computing for Healthcare
(2021)
Pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. However, most pretraining efforts focus on general domain corpora, such as newswire and Web. A prevailing a...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3458754
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
Sebastian Ruder • Arrow@dit (Dublin Institute of Technology)
(2019)
The current generation of neural network-based natural language processing models excels at learning from large amounts of labelled data. Given these capabilities, natural language processing is increasingly applied to new tasks, new domain...
OPENALEX
Open Access
DOI: https://doi.org/10.13025/17598
Jingmin An, Xiaogang Weng • BMC Bioinformatics
(2022)
Abstract Pre-trained natural language processing models on a large natural language corpus can naturally transfer learned knowledge to protein domains by fine-tuning specific in-domain tasks. However, few studies focused on enriching such p...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12859-022-05031-z
Wei Huang, Xingyu Zheng, Xudong Ma, Haotong Qin et al. • Visual Intelligence
(2024)
Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44267-024-00070-x
Direselign Addis Tadesse, Chuan-Ming Liu, Van-Dai Ta • Applied Sciences
(2020)
Reading text and unified text detection and recognition from natural images are the most challenging applications in computer vision and document analysis. Previously proposed end-to-end scene text reading methods do not consider the freque...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app10134474
Xiaolong Ma, Peishun Liu, Haojie Gao, Zikang Yan et al. • IEEE Access
(2025)
In the fields of natural language processing and computer vision, the emergence of large pre-trained models has led to the adoption of fine-tuning them for downstream tasks as an important paradigm. However, the full fine-tuning approach of...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3529807
Lu Yuan, Dongdong Chen, Yi‐Ling Chen, Noel Codella et al. • arXiv (Cornell University)
(2021)
Automated visual understanding of our diverse and open world demands computer vision models to generalize well with minimal customization for specific tasks, similar to human vision. Computer vision foundation models, which are trained on d...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.2111.11432
Hong-hui Xu, Xin-qing Wang, Dong Wang, Bao-guo Duan et al. • Defence Technology
(2023)
Detecting highly-overlapped objects in crowded scenes remains a challenging problem, especially for one-stage detector. In this paper, we extricate YOLOv4 from the dilemma in a crowd by fine-tuning its detection scheme, named YOLO-CS. Speci...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.dt.2021.10.007
Xiaozheng Li, Huazhen Wang, Huixin He, Jixiang Du et al. • BMC Bioinformatics
(2019)
Abstract Background Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural n...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12859-019-2617-8
Chia-Chin Chuang, Zheng-Wei Lin Chi, Tzu-Chien Kuo, Che-Jui Chang et al. • Machines
(2026)
Structural aging and environmental changes associated with long-term operation can substantially modify the thermal behavior of machine tools, diminishing the accuracy of existing thermal compensation models. Traditional neural network appr...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/machines14030309
Buhong Wang, Jin Xiao, Ruochen Dong, Chengkai Piao et al. • Aerospace
(2026)
Satellite networks are essential to global connectivity yet face severe multidimensional cybersecurity threats. This systematic review conducts a holistic analysis of threats across the physical, network, and user layers. We propose the Sat...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/aerospace13030249