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Showing 20 of 2,986 academic articles

Identifying urban villages using graph neural network and transfer learning in Southern Jiangsu, China

Zhenkang Wang, Nan Xia, Jiale Liang, Jiechen Wang • Geo-spatial Information Science (2026)

China’s rapid urbanization has led to the emergence of urban villages (UVs), whose governance is crucial for urban quality and built environment management. However, conventional identification methods rely on high-resolution remote sensing...

DOAJ Open Access (DOAJ) DOI: 10.1080/10095020.2026.2711549

A Space-Time Partial Differential Equation Based Physics-Guided Neural Network for Sea Surface Temperature Prediction

Taikang Yuan, Junxing Zhu, Wuxin Wang, Jingze Lu et al. • Remote Sensing (2023)

Sea surface temperature (SST) prediction has attracted increasing attention, due to its crucial role in understanding the Earth’s climate and ocean system. Existing SST prediction methods are typically based on either physics-based numerica...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs15143498

Design of a TSR-based project learning strategy for biochemistry undergraduate teaching and research labs: a case study

Camille R. Reaux, Shelby A. Meche, Jordan M. Grider, Soundharya Dhanabal et al. • Frontiers in Education (2025)

Given the exponential growth of biochemical data and deep effect of computational methods on life sciences, there is a need to rethink undergraduate curricula. A project-oriented learning approach based on the Triangular Spatial Relationshi...

DOAJ Open Access (DOAJ) DOI: 10.3389/feduc.2024.1455173

Providing a framework for designing electronic and virtual learning environments based on the principles and criteria of cognitive flexibility

Z. Karami • Fanāvarī-i āmūzish (2023)

Background and Objectives: In order to solve the problem of education in complex and unstructured domains, Spiro and his colleagues proposed the theory of cognitive flexibility, in which they advocated multiple forms of pedagogical models, ...

DOAJ Open Access (DOAJ) DOI: 10.22061/tej.2023.9686.2885

A Review of Deep Learning Applications in Intrusion Detection Systems: Overcoming Challenges in Spatiotemporal Feature Extraction and Data Imbalance

Ya Zhang, Ravie Chandren Muniyandi, Faizan Qamar • Applied Sciences (2025)

In the rapid development of the Internet of Things (IoT) and large-scale distributed networks, Intrusion Detection Systems (IDS) face significant challenges in handling complex spatiotemporal features and addressing data imbalance issues. T...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15031552

Automated Website Fingerprinting through Deep Learning

Vera Rimmer, Davy Preuveneers, Marc Juarez, Tom Van Goethem et al. • Network and Distributed System Security Symposium (2018)

Several studies have shown that the network traffic that is generated by a visit to a website over Tor reveals information specific to the website through the timing and sizes of network packets.By capturing traffic traces between users and...

OPENALEX Open Access DOI: https://doi.org/10.14722/ndss.2018.23105

Accuracy of machine learning for differentiation between optic neuropathies and pseudopapilledema

Jin Mo Ahn, Sangsoo Kim, Kwang-Sung Ahn, Sung-Hoon Cho et al. • BMC Ophthalmology (2019)

Abstract Background This study is to evaluate the accuracy of machine learning for differentiation between optic neuropathies, pseudopapilledema (PPE) and normals. Methods Two hundred and ninety-five images of optic neuropathies, 295 images...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12886-019-1184-0

An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders

Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan et al. • BMC Psychiatry (2025)

Abstract Background Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional s...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12888-025-07196-2

Computational Hyperspectral Camera Design Based on Co-Modulation of Diffractive Optical Element and Superposition Fabry-Perot Filter Array

Shiqi Feng, Xuquan Wang, Xiong Dun, Zhanshan Wang et al. • IEEE Photonics Journal (2025)

Encoded computational hyperspectral cameras, propelled by advances in compressed sensing theory, making both miniaturization and real-time hyperspectral imaging feasible. Spectral-encoded or spatial-encoded hyperspectral imaging strategy ha...

DOAJ Open Access (DOAJ) DOI: 10.1109/JPHOT.2025.3624799

Deep-learning–based non-contrast CT for detecting acute ischemic stroke: a systematic review and HSROC meta-analysis of patient-level diagnostic accuracy

Kalab Yigermal Gete, Asnakew Achaw Ayele • BMC Neurology (2025)

Abstract Background Non-contrast CT (NCCT) is first-line imaging for suspected acute ischemic stroke (AIS) but has limited early sensitivity; deep learning (DL) may improve patient-level detection. Objectives To estimate the diagnostic accu...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12883-025-04528-3

Evaluating the Accuracy of Deep Learning Models and Dental Postgraduate Students in Measuring Working Length on Intraoral Periapical X-rays: An In vitro Study

R. S. Basavanna, Ishaan Adhaulia, N. M. Dhanyakumar, Jyoti Joshi • Contemporary Clinical Dentistry (2025)

Background: The integration of artificial intelligence in dentistry has seen remarkable advancements, especially in diagnostic imaging. This study evaluates and compares the accuracy of deep learning models with that of dental postgraduate ...

DOAJ Open Access (DOAJ) DOI: 10.4103/ccd.ccd_274_24

Ethical and legal concerns in artificial intelligence applications for the diagnosis and treatment of lung cancer: a scoping review

Ghenwa Chamouni, Filippo Lococo, Carolina Sassorossi, Nkunzi Atuhaire et al. • Frontiers in Public Health (2025)

IntroductionArtificial intelligence (AI) is increasingly integrating into the healthcare field, particularly in lung cancer care, including screening, diagnosis, treatment, and prognosis. While these applications offer promising advancement...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpubh.2025.1663298

Deep learning in medical image registration: a review

Yabo Fu, Yang Lei, Tonghe Wang, Walter John Curran et al. • Physics in Medicine and Biology (2020)

This paper presents a review of deep learning (DL)-based medical image registration methods. We summarized the latest developments and applications of DL-based registration methods in the medical field. These methods were classified into se...

OPENALEX Open Access DOI: https://doi.org/10.1088/1361-6560/ab843e PMC: 7759388

Supervised Speech Separation Based on Deep Learning: An Overview

DeLiang Wang, Jitong Chen • IEEE/ACM Transactions on Audio Speech and Language Processing (2018)

Speech separation is the task of separating target speech from background interference. Traditionally, speech separation is studied as a signal processing problem. A more recent approach formulates speech separation as a supervised learning...

OPENALEX Open Access DOI: https://doi.org/10.1109/taslp.2018.2842159 PMC: 6586438

Deep Learning for Portfolio Optimization

Zihao Zhang, Stefan Zohren, Stephen Roberts • The Journal of Financial Data Science (2020)

In this article, the authors adopt deep learning models to directly optimize the portfolio Sharpe ratio. The framework they present circumvents the requirements for forecasting expected returns and allows them to directly optimize portfolio...

OPENALEX Open Access DOI: https://doi.org/10.3905/jfds.2020.1.042

Deep learning improves antimicrobial peptide recognition

Daniel Veltri, Uday Kamath, Amarda Shehu • Bioinformatics (2018)

Motivation: Bacterial resistance to antibiotics is a growing concern. Antimicrobial peptides (AMPs), natural components of innate immunity, are popular targets for developing new drugs. Machine learning methods are now commonly adopted by w...

OPENALEX cc-by-nc DOI: https://doi.org/10.1093/bioinformatics/bty179 PMC: 6084614

Scalable and accurate deep learning with electronic health records

Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai et al. • npj Digital Medicine (2018)

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variabl...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41746-018-0029-1 PMC: 6550175

Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint

Michael Kloster, Andrea M. Burfeid-Castellanos, Daniel Langenkämper, Tim W. Nattkemper et al. • PLoS ONE (2023)

Diatoms represent one of the morphologically and taxonomically most diverse groups of microscopic eukaryotes. Light microscopy-based taxonomic identification and enumeration of frustules, the silica shells of these microalgae, is broadly us...

DOAJ Open Access (DOAJ)