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An Analysis of the Training Data Impact for Domain-Adapted Tokenizer Performances—The Case of Serbian Legal Domain Adaptation

Miloš Bogdanović, Milena Frtunić Gligorijević, Jelena Kocić, Leonid Stoimenov • Applied Sciences (2025)

Various areas of natural language processing (NLP) have greatly benefited from the development of large language models in recent years. This research addresses the challenge of developing efficient tokenizers for transformer-based domain-s...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15137491

Cracking the code: AI’s role in mapping evidence syntheses to the United Nations sustainable development goals

Bianca Pilla, Jennifer Stone, Zoe Jordan • Archives of Public Health (2025)

Abstract Background Understanding the alignment and contributions of research to the United Nations Sustainable Development Goals (UN SDGs) is essential for guiding global progress toward these critical targets. Several SDG mapping approach...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13690-025-01784-0

Valorisation of agri-food by-products into bioactive compounds: Green extraction, microbial biotransformation and circular biorefinery strategies

Arjun Mohanakumar, Massimiliano Rinaldi, Jasmine Hadj Saadoun, Camilla Lazzi et al. • Applied Food Research (2026)

Agri-food processing generates large volumes of by-products that remain insufficiently exploited despite their content of phenolic compounds, peptides, polysaccharides, carotenoids, dietary fibres and other functional constituents. These si...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.afres.2026.102511

Datasets: A Community Library for Natural Language Processing

Quentin Lhoest, A. Villanova del Moral, Yacine Jernite, Abhishek Thakur et al. • Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP) (2021)

Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, Abhishek Thakur, Patrick von Platen, Suraj Patil, Julien Chaumond, Mariama Drame, Julien Plu, Lewis Tunstall, Joe Davison, Mario Šaško, Gunjan Chhablani, Bhavitvya Malik, Simon Bra...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/2021.emnlp-demo.21

Analysis and Classification of Word Co-Occurrence Networks From Alzheimer’s Patients and Controls

Tristan Millington, Saturnino Luz • Frontiers in Computer Science (2021)

In this paper we construct word co-occurrence networks from transcript data of controls and patients with potential Alzheimer’s disease using the ADReSS challenge dataset of spontaneous speech. We examine measures of the structure of these ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcomp.2021.649508

Transfer Learning in Natural Language Processing

Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, Thomas Wolf (2019)

The classic supervised machine learning paradigm is based on learning in isolation, a single predictive model for a task using a single dataset. This approach requires a large number of training examples and performs best for well-defined a...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/n19-5004

Natural language processing with Python

Steven Bird, Ewan Klein, Edward Loper • CERN Document Server (European Organization for Nuclear Research) (2009)

This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'...

OPENALEX

Unpacking Public Perceptions of Qris with Twitter Data: A Vader And LDA Methodology

Dzakiya Ishmatul Ulya, Anang Kunaefi, Dwi Rolliawati, Bayu Adhi Nugroho • Jurnal ELTIKOM: Jurnal Teknik Elektro, Teknologi Informasi dan Komputer (2023)

QRIS, a mobile payment transaction system standardized by Bank Indonesia, has become the subject of extensive public discourse on Twitter. Employing VADER for sentiment analysis and LDA for topic modeling, this study aims to capture the nua...

DOAJ Open Access (DOAJ) DOI: 10.31961/eltikom.v7i2.742

Documenting Computer Vision Datasets

Milagros Miceli, Tianling Yang, Laurens Naudts, Martin Schuessler et al. • ACM Conference on Fairness, Accountability, and Transparency (FAccT) (2021)

In industrial computer vision, discretionary decisions surrounding the production of image training data remain widely undocumented. Recent research taking issue with such opacity has proposed standardized processes for dataset documentatio...

OPENALEX cc-by DOI: https://doi.org/10.1145/3442188.3445880

Artificial intelligence-based masked face detection: A survey

Khalid M. Hosny, Nada AbdElFattah Ibrahim, Ehab R. Mohamed, Hanaa M. Hamza • Intelligent Systems with Applications (2024)

The COVID-19 virus is causing a global pandemic. The total number of new coronavirus cases worldwide by the end of November 2020 had already surpassed 60 million. The World Health Organization (WHO) has determined that wearing masks is a cr...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.iswa.2024.200391

A comprehensive survey on RGB-D-based human action recognition: algorithms, datasets, and popular applications

Yumin Zhang, Yanyong Wang • EURASIP Journal on Image and Video Processing (2025)

Abstract Due to the rapid advances in computer vision and deep learning, human action recognition has become one of the most important representative tasks for video understanding. Especially for human action recognition based on RGB-D data...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13640-025-00677-0

Mobile system for road sign detection and recognition with template matching

Maćkowski Michał, Sawiski Michał, Walczyszyn Wojciech • MATEC Web of Conferences (2019)

This paper explores the effective approach to road sign detection and recognition based on mobile devices. Detecting and recognising road signs is a challenging matter because of different shapes, complex background and irregular sign illum...

DOAJ Open Access (DOAJ) DOI: 10.1051/matecconf/201925203014

Automated Burr Quality Classification in Drilling of AA6013 Aluminum Alloy Using YOLOv10n

Mikail Kırğıl, Suleyman Gokhan Taskin, Ali Ercetin • Applied Sciences (2026)

Burr formation during drilling of aluminum alloys can compromise hole quality and assembly accuracy, increasing the need for secondary deburring operations. The time-consuming and operator-dependent nature of manual visual inspection create...

DOAJ Open Access (DOAJ) DOI: 10.3390/app162010012

Identification of camouflage military individuals with deep learning approaches DFAN and SINETV2

Ali Haider, Ghulam Muhammad, Talha Ahmed Khan, Kushsairy Kadir et al. • Scientific Reports (2025)

Abstract Camouflaged object detection particularly is considered as challenging and crucial because these objects are designed to either mimic their environment or be completely hidden within it. The goal of camouflage patterns utilization ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-18886-y

Transformer in Computer Vision

Jiarui Bi, Zengliang Zhu, Qinglong Meng • International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI) (2021)

Transformer is widely used in Natural Language Processing (NLP), in which numerous papers have been proposed. Recently, the transformer has been borrowed for many computer vision tasks. However, there are few papers to give a comprehensive ...

OPENALEX DOI: https://doi.org/10.1109/cei52496.2021.9574462

Computer Vision System for Automatic Counting of Planting Microsites Using UAV Imagery

Wassim Bouachir, Koffi Eddy Ihou, Houssem-Eddine Gueziri, Nizar Bouguila et al. • IEEE Access (2019)

Mechanical site preparation by mounding is often used by the forest industry to provide optimal growth conditions for tree seedlings. Prior to planting, an essential step consists in estimating the number of mounds at each planting block, w...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2923765