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Modernizing GNSS data acquisition, pre-processing, and distribution at volcanological observatories

P. Sakic, P. Boissier, P. Boissier, J.-M. Saurel et al. • Geoscientific Instrumentation, Methods and Data Systems (2026)

In recent years, the field of geodetic monitoring is undergoing a profound transformation driven by the transition from GPS-only positioning to a fully multi-GNSS environment. With Galileo, BeiDou, and modernized GPS & GLONASS constella...

DOAJ Open Access (DOAJ) DOI: 10.5194/gi-15-89-2026

Quantum transfer learning for cross-domain cybersecurity threat detection and categorization

Shtwai Alsubai, Mohamed Ayari, Natalia Kryvinska, Ahmad Almadhor et al. • Scientific Reports (2026)

Abstract Cybersecurity challenges have become increasingly complex and widespread, and the risks associated with these problems are substantial, affecting thousands of individuals and organisations and being crucial to national security. As...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-40634-z

A neural-network-based detection of epilepsy

Vivek Prakash Nigam, Daniel Graupe • Neurological Research (2004)

Diagnosis of epilepsy is primarily based on scalp-recorded electroencephalograms (EEG). Unfortunately the long-term recordings obtained from 'ambulatory recording systems' contain EEG data of up to one week duration, which has introduced ne...

OPENALEX DOI: https://doi.org/10.1179/016164104773026534

The Effectiveness of Arabic Stemmers Using Arabized Word Removal

Hamood ALshalabi, Sabrina Tiun, Nazlia Omar, Kamal Ali Alezabi et al. • International Journal of Information Science and Management (2022)

Other languages have influenced Arabic because of several factors, such as geographical nearness, trade communication, past Islamic conquests, science and technology, new devices, brand names, models, and fashion. As a result of these facto...

DOAJ Open Access (DOAJ)

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

Segmentation of muscle tissue in computed tomography images at the level of the L3 vertebra

A. R. Teplyakova, R. V. Shershnev, S. O. Starkov, V. A. Kukarskaya • Научно-технический вестник информационных технологий, механики и оптики (2024)

With the increasing routine workload on radiologists associated with the need to analyze large numbers of images, there is a need to automate part of the analysis process. Sarcopenia is a condition in which there is a loss of muscle mass. T...

DOAJ Open Access (DOAJ) DOI: 10.17586/2226-1494-2024-24-1-124-132

Estimating Black Oat Biomass Using Digital Surface Models and a Vegetation Index Derived from RGB-Based Aerial Images

Lucas Renato Trevisan, Lisiane Brichi, Tamara Maria Gomes, Fabrício Rossi • Remote Sensing (2023)

Responsible for food production and industry inputs, agriculture needs to adapt to worldwide increasing demands and environmental requirements. In this scenario, black oat has gained environmental and economic importance since it can be use...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs15051363

Effectual pre-processing with quantization error elimination in pose detector with the aid of image-guided progressive graph convolution network (IGP-GCN) for multi-person pose estimation

Jhansi Rani Challapalli, Nagaraju Devarakonda • Machine Learning: Science and Technology (2023)

Multi-person pose estimation (MPE) remains a significant and intricate issue in computer vision. This is considered the human skeleton joint identification issue and resolved by the joint heat map regression network lately. Learning robust ...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-2153/acc9fc

Computer Vision Techniques in Manufacturing

Longfei Zhou, Zhang Li, Nicholas Konz • IEEE Transactions on Systems Man and Cybernetics Systems (2022)

Computer vision techniques have played an important role in promoting the informatization, digitization and intelligence of industrial manufacturing systems. Considering the rapid development of computer vision techniques, we present a comp...

OPENALEX Open Access DOI: https://doi.org/10.1109/tsmc.2022.3166397

Computer vision for microscopy diagnosis of malaria

Faik Boray TEK, Andrew Graham Dempster, İzzet Kale • Malaria Journal (2009)

This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or prop...

OPENALEX cc-by DOI: https://doi.org/10.1186/1475-2875-8-153 PMC: 2719653

Data Efficient Vision Transformer Based Model for Brain Tumor Classification in MRI

Vinodkumar Patil, Manisha Patil, Smital Patil, Satish Desale • Advances in Engineering and Intelligence Systems (2026)

Accurate detection of brain tumors at early stages is crucial for clinical diagnosis and treatment planning. Magnetic Resonance Imaging (MRI) is the most popular method due to its soft-tissue contrast and spatial resolution. However, manual...

DOAJ Open Access (DOAJ) DOI: 10.22034/aeis.2026.570662.1424

A Survey on Deep Learning for Software Engineering

Yanming Yang, Xin Xia, David Lo, John Grundy • ACM Computing Surveys (2021)

In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)” and an improved model training method to break the bottleneck of neural network development. More recently, the introduction of AlphaGo in 2016 demonstr...

OPENALEX Open Access DOI: https://doi.org/10.1145/3505243

Deep learning-based recognition and segmentation of intracranial aneurysms under small sample size

Guangyu Zhu, Xueqi Luo, Tingting Yang, Li Cai et al. • Frontiers in Physiology (2022)

The manual identification and segmentation of intracranial aneurysms (IAs) involved in the 3D reconstruction procedure are labor-intensive and prone to human errors. To meet the demands for routine clinical management and large cohort studi...

DOAJ Open Access (DOAJ) DOI: 10.3389/fphys.2022.1084202

Deep metabolome: Applications of deep learning in metabolomics

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...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.csbj.2020.09.033 PMC: 7575644

A deep learning-driven pipeline for differentiating hypertrophic cardiomyopathy from cardiac amyloidosis using 2D multi-view echocardiography

Xiaofeng Li, Bo Peng, Xinyu Li, Zhenghan Wang et al. • Scientific Reports (2026)

Abstract Hypertrophic Cardiomyopathy (HCM) and Cardiac Amyloidosis (CA) are two cardiac conditions that can advance to heart failure if left untreated, which present considerable diagnostic challenges due to their overlapping echocardiograp...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-15443-5

Review of Deep Learning for Language Modeling

WANG Sili, ZHANG Ling, YANG Heng, LIU Wei • Nongye tushu qingbao xuebao (2023)

[Purpose/Significance] Deep learning for language modeling is one of the major methods and advanced technologies to enhance language intelligence of machines at present, which has become an indispensable important technical means for automa...

DOAJ Open Access (DOAJ) DOI: 10.13998/j.cnki.issn1002-1248.23-0251

Fairness in Machine Learning: A Survey

Simon J. Caton, Christian Stefan Haas • ACM Computing Surveys (2023)

When Machine Learning technologies are used in contexts that affect citizens, companies as well as researchers need to be confident that there will not be any unexpected social implications, such as bias towards gender, ethnicity, and/or pe...

OPENALEX cc-by DOI: https://doi.org/10.1145/3616865

Predicting Stock Price Movements with Combined Deep Learning Models and Two-Tier Metaheuristic Optimization Algorithm

Khalil A. Alruwaitee • Journal of Radiation Research and Applied Sciences (2024)

Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrras.2024.101172