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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

Face recognition with Bayesian convolutional networks for robust surveillance systems

Umara Zafar, Mubeen Ghafoor, Tehseen Zia, Ghufran Ahmed et al. • EURASIP Journal on Image and Video Processing (2019)

Abstract Recognition of facial images is one of the most challenging research issues in surveillance systems due to different problems including varying pose, expression, illumination, and resolution. The robustness of recognition method st...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13640-019-0406-y

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

Understanding the role of autoencoders for stiff dynamical systems using information theory

Vijayamanikandan Vijayarangan, Harshavardhana A. Uranakara, Francisco E. Hernández–Pérez, Hong G. Im • Energy and AI (2025)

Using information theory, this study provides insights into how the construction of latent space of autoencoder (AE) using deep neural network (DNN) training finds a smooth (non-stiff) low-dimensional manifold in the stiff dynamical system....

DOAJ Open Access (DOAJ) DOI: 10.1016/j.egyai.2025.100567

A Novel Methodology for Human Kinematics Motion Detection Based on Smartphones Sensor Data Using Artificial Intelligence

Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh, Raed Abu Zitar et al. • Technologies (2023)

Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily li...

DOAJ Open Access (DOAJ) DOI: 10.3390/technologies11020055

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

A Comprehensive Survey on Graph Anomaly Detection With Deep Learning

Xiaoxiao Ma, Jia Xin Wu, Shan Xue, Jian Yu Yang et al. • IEEE Transactions on Knowledge and Data Engineering (2021)

Anomalies are rare observations (e.g., data records or events) that deviate significantly from the others in the sample. Over the past few decades, research on anomaly mining has received increasing interests due to the implications of thes...

OPENALEX Open Access DOI: https://doi.org/10.1109/tkde.2021.3118815

Deep learning in omics: a survey and guideline

Zhiqiang Zhang, Yi Chen Zhao, Xiangke Liao, Wenqiang Shi et al. • Briefings in Functional Genomics (2018)

Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fo...

OPENALEX DOI: https://doi.org/10.1093/bfgp/ely030

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

Hierarchical Multimodal Sleep Staging with Optimized EEG, EOG, and PPG Features for Wearable Applications

Roberto De Fazio, Matteo Paiano, Ramiro Velazquez, Carolina Del-Valle-Soto et al. • Applied Sciences (2026)

Automatic sleep staging is fundamental for diagnosing sleep disorders and enabling long-term sleep monitoring with wearable devices. Although Deep Learning has significantly improved classification performance, balancing accuracy with compu...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16168164

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

Quantum Leap in Healthcare: A Comparative Analysis of AI/ML and Quantum Computing for Healthcare opportunities of the new era

salma mostafa ahmed helmy, Salsabil Amin, Abeer mahmoud, El-Sayed El-Horabty • International Journal of Intelligent Computing and Information Sciences (2026)

The healthcare sector is undergoing rapid transformation driven by advances in artificial intelligence and machine learning, with quantum computing emerging as the next major breakthrough. This paper presents a comparative analysis of class...

DOAJ Open Access (DOAJ) DOI: 10.21608/ijicis.2026.442636.1439

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

Condensing AI-Based Attitude Control Using Kolmogorov–Arnold Networks for Memory Efficiency

Kirill Djebko, Patrick Schurk, Tom Baumann, Frank Puppe et al. • Aerospace (2025)

Artificial Intelligence (AI) is rapidly transforming engineering fields, from robotics to aerospace, with applications in control systems for UAVs and satellites. This work builds on a previously developed AI attitude controller for the Inn...

DOAJ Open Access (DOAJ) DOI: 10.3390/aerospace12121039

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

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

A Deep Learning Approach for Network Intrusion Detection System

Ahmad Y. Javaid, Quamar Niyaz, Weiqing Sun, Mansoor Alam • International Conference on Bio-Inspired Models of Network, Information and Computing Systems (BIONETICS) (2016)

A Network Intrusion Detection System (NIDS) helps system administrators to detect network security breaches in their organizations. However, many challenges arise while developing a flexible and efficient NIDS for unforeseen and unpredictab...

OPENALEX cc-by DOI: https://doi.org/10.4108/eai.3-12-2015.2262516

On the Origin of Deep Learning

Haohan Wang, Bhiksha Raj • arXiv (Cornell University) (2017)

This paper is a review of the evolutionary history of deep learning models. It covers from the genesis of neural networks when associationism modeling of the brain is studied, to the models that dominate the last decade of research in deep ...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1702.07800