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Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey

Michela Prunella, Roberto Maria Scardigno, Domenico Buongiorno, Antonio Brunetti et al. • IEEE Access (2023)

Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3271748

Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network

Johannes Leiner, Vincent Pellissier, Sebastian König, Sven Hohenstein et al. • Respiratory Research (2022)

Abstract Background Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both i...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12931-022-02180-w

Exploring the Impact of Alternatives of Object-Oriented Cohesion Measures on Machine Learning-Based Predictions of Inheritance Reusability

Jehad Al Dallal, Bader Alkhazi • IEEE Access (2024)

The cohesion of an object-oriented class refers to the relatedness of its methods and attributes. Constructors, destructors, and access methods are special types of methods featuring unique characteristics that can artificially affect class...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3484007

Effect of Word Sense Disambiguation on Neural Machine Translation: A Case Study in Korean

Quang-Phuoc Nguyen, Anh-Dung Vo, Joon-Choul Shin, Cheol-Young Ock • IEEE Access (2018)

With the advent of robust deep learning, neural machine translation (NMT) has achieved great progress and recently become the dominant paradigm in machine translation (MT). However, it is still confronted with the challenge of word ambiguit...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2018.2851281

Defining artificial intelligence for librarians

Andrew Martin Cox, Suvodeep Mazumdar A • Journal of Librarianship and Information Science (2022)

The aim of the paper is to define Artificial Intelligence (AI) for librarians by examining general definitions of AI, analysing the umbrella of technologies that make up AI, defining types of use case by area of library operation, and then ...

OPENALEX cc-by DOI: https://doi.org/10.1177/09610006221142029

Neurosurgery and artificial intelligence

Mohammad Mofatteh • AIMS neuroscience (2021)

Neurosurgeons receive extensive and lengthy training to equip themselves with various technical skills, and neurosurgery require a great deal of pre-, intra- and postoperative clinical data collection, decision making, care and recovery. Th...

OPENALEX cc-by DOI: https://doi.org/10.3934/neuroscience.2021025 PMC: 8611194

Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges

Luciellen da Costa Ferreira, Ian Carlos Bispo Carvalho, Lúcio André de Castro Jorge, Alice Maria Quezado-Duval et al. • Frontiers in Plant Science (2024)

Food security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpls.2024.1387925

Virtual reality in skill development through user experience and technology advancements

Mochammad Hannats Hanafi Ichsan, Cecilia Sik-Lanyi, Tibor Guzsvinecz • Discover Computing (2025)

Abstract New technologies, such as Virtual Reality (VR) / Virtual Environment (VE), which focus on User Experience (UX) to provide more engaging and immersive experiences, can help people grow their skills. Technology advancement is also an...

DOAJ Open Access (DOAJ) DOI: 10.1007/s10791-025-09703-1

Introducing Artificial Intelligence Training in Medical Education

Ketan Paranjape, Michiel Schinkel, Rishi S. Nannan Panday, Josip Car et al. • JMIR Medical Education (2019)

Health care is evolving and with it the need to reform medical education. As the practice of medicine enters the age of artificial intelligence (AI), the use of data to improve clinical decision making will grow, pushing the need for skillf...

OPENALEX cc-by DOI: https://doi.org/10.2196/16048 PMC: 6918207

Ranking-Based Case Retrieval with Graph Neural Networks in Process-Oriented Case-Based Reasoning

Maximilian Hoffmann, Ralph Bergmann • Proceedings of the International Florida Artificial Intelligence Research Society Conference (2023)

In Process-Oriented Case-Based Reasoning (POCBR), experiential knowledge from previous problem-solving situations is retrieved from a case base to be reused for upcoming problems. The task of retrieval is approached in previous work by usin...

DOAJ Open Access (DOAJ) DOI: 10.32473/flairs.36.133039

Unified Multimodal Information Flows for Immersive and Context-Aware 6G Systems

Rajesh Manoharan, R. V. Siva Balan, G. Govinda Rajulu, Amit Kumar Padhy et al. • IEEE Open Journal of the Communications Society (2026)

Communication is moving from being data-centric to being experience-centric and perception-aware with the advent of 6G wireless networks. Immersive applications such as digital twins, holographic telepresence, extended reality, tactile Inte...

DOAJ Open Access (DOAJ) DOI: 10.1109/OJCOMS.2026.3683716

SSMSFuse: A Spectral and Spatial Multiscale Coupling Fusion Model for Hyperspectral and Multispectral Image

Siyuan Liu, Yingchao Fan, Qi Hu, Bing Li et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2025)

Hyperspectral image (HSI) has more spectral information than conventional images, which helps to distinguish targets in a complex scene more accurately. However, HSI typically has a low spatial resolution, which limits their application sce...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2025.3586076

Prototype-oriented contrastive mean-teacher for unsupervised domain adaptive object detection

Qi Cao, Jianwen Tao, Yufang Dan, Di Zhou • Scientific Reports (2026)

Abstract Unsupervised domain adaptive object detection (UDA-OD) aims to deploy a detector trained on source domain(s) to a new, unlabeled target domain. Carrying out mean-teacher self-training for UDA-OD poses a significant challenge, given...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-44991-7

Economic Evaluations of Artificial Intelligence Implementation in Diabetic Retinopathy Screening

Ahmad Ahmad, Neily Zakiyah, Auliya A. Suwantika • Pharmacology and Clinical Pharmacy Research (2025)

Diabetic retinopathy (DR) is a common complication of diabetes that damages retinal blood vessels and can lead to vision impairment. The application of Artificial Intelligence (AI) in DR screening offers a promising alternative to conventio...

DOAJ Open Access (DOAJ) DOI: 10.15416/pcpr.v9i3.60068

Artificial Intelligence for Games

Ian Millington, John Funge • CRC Press eBooks (2018)

Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional ex...

OPENALEX DOI: https://doi.org/10.1201/9781315375229

Artificial Intelligence for Games

Ian Millington • CRC Press eBooks (2009)

Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional ex...

OPENALEX DOI: https://doi.org/10.1201/b13169

Design of the Digital Pathology Workspace for Artificial Intelligence Integration

Elena Guerini-Rocco, Chiara Frascarelli, Joana Sorino, Francesca Maria Porta et al. • Applied Sciences (2026)

Designing an optimal digital pathology workspace is essential to ensure diagnostic accuracy and safeguard the long-term well-being of pathologists. While digital pathology improves reproducibility, facilitates multidisciplinary collaboratio...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16126021

Adaptive habitat biogeography-based optimizer for optimizing deep CNN hyperparameters in image classification

Jiayun Xin, Mohammad Khishe, Diyar Qader Zeebaree, Laith Abualigah et al. • Heliyon (2024)

Deep Convolutional Neural Networks (DCNNs) have shown remarkable success in image classification tasks, but optimizing their hyperparameters can be challenging due to their complex structure. This paper develops the Adaptive Habitat Biogeog...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.heliyon.2024.e28147