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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

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

ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning

Sarah Alhumoud, Asma Al Wazrah, Laila Alhussain, Lama Alrushud et al. • PeerJ Computer Science (2023)

COVID-19 has become a global pandemic that has affected not only the health sector but also economic, social, and psychological well-being. Individuals are using social media platforms to communicate their feelings and sentiments about the ...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.1507

An Ownership Verification Mechanism Against Encrypted Forwarding Attacks in Data-Driven Social Computing

Zhe Sun, Junping Wan, Bin Wang, Zhiqiang Cao et al. • Frontiers in Physics (2021)

Data-driven deep learning has accelerated the spread of social computing applications. To develop a reliable social application, service providers need massive data on human behavior and interactions. As the data is highly relevant to users...

DOAJ Open Access (DOAJ) DOI: 10.3389/fphy.2021.739259

Behavioral Motivation and Influencing Factors of Graduate Students Using AIGC Tool: An Empirical Analysis Based on Questionnaire Survey

Yijia WAN, Liping GU • Nongye tushu qingbao xuebao (2024)

[Purpose/Significance] To explore in depth the acceptance and usage habits of AIGC tools by graduate students in the process of academic research, and to promote the positive attention and application of emerging technologies by graduate st...

DOAJ Open Access (DOAJ) DOI: 10.13998/j.cnki.issn1002-1248.24-0716

Deep Learning for Spatio-Temporal Data Mining: A Survey

Senzhang Wang, Jiannong Cao, Philip S. Yu • IEEE Transactions on Knowledge and Data Engineering (2020)

With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from spatio-temp...

OPENALEX Open Access DOI: https://doi.org/10.1109/tkde.2020.3025580

Understanding tourist engagement with traditional dwellings through multimodal deep learning: a case study of the Gao Family Compound, Xi’an

Liyue Wu, Qinchuan Zhan, Yanjun Li • Humanities & Social Sciences Communications (2026)

Abstract This study applies a multimodal deep learning approach to examine tourist engagement with traditional architectural heritage. The Gao Family Compound in Xi’an serves as a representative case. Social-media texts and images from Weib...

DOAJ Open Access (DOAJ) DOI: 10.1057/s41599-026-07879-5

A longitudinal study on students’ self-regulated listening during transition to an English-medium transnational university in China

Sihan Zhou, Gene Thompson • Studies in Second Language Learning and Teaching (2023)

Listening to academic content in English medium instruction (EMI) classrooms at university can be a demanding task for students who transition from first language (L1) instructed secondary schools. This longitudinal mixed methods study anal...

DOAJ Open Access (DOAJ) DOI: 10.14746/ssllt.38281

Bi-Objective Portfolio Optimization Under ESG Volatility via a MOPSO-Deep Learning Algorithm

Imma Lory Aprea, Gianni Bosi, Gabriele Sbaiz, Salvatore Scognamiglio • Mathematics (2025)

In this paper, we tackle a bi-objective optimization problem in which we aim to maximize the portfolio diversification and, at the same time, minimize the portfolio volatility, where the ESG (Environmental, Social, and Governance) informati...

DOAJ Open Access (DOAJ) DOI: 10.3390/math13203308

A Survey on Deep Learning for Human Mobility

Massimiliano Luca, Gianni Barlacchi, Bruno Lepri, Luca Pappalardo • ACM Computing Surveys (2021)

The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS t...

OPENALEX Open Access DOI: https://doi.org/10.1145/3485125

Identifying private pumping wells in a land subsidence area in Taiwan using deep learning technology and street view images

Chun-Wei Huang, Si Ying Yau, Chiao-Ling Kuo, Tsai-Yu Kuan et al. • Journal of Hydrology: Regional Studies (2024)

Study region: The Choushui River Fan, Taiwan. Study focus: Groundwater overdraft has led to not only groundwater depletion but also environmental disasters, such as subsidence and seawater intrusion in the Choushui River Alluvial Fan, Taiwa...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ejrh.2023.101636

Siamese text classification network (SiamTCN) for multi-class multi-label information extraction of typhoon disasters from social media data

Zhi He, Chengle Zhou, Liwei Zou, Suhong Zhou et al. • International Journal of Digital Earth (2025)

Accurately monitoring disaster effects is a crucial task in relief efforts (e.g. typhoon rescue). Social media data plays a vital role in disaster management, while deep learning-based methods gain more attention in typhoon disaster researc...

DOAJ Open Access (DOAJ) DOI: 10.1080/17538947.2025.2517790

A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images

Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza et al. • BMC Medical Informatics and Decision Making (2025)

Abstract Deep learning has significantly contributed to medical imaging and computer-aided diagnosis (CAD), providing accurate disease classification and diagnosis. However, challenges such as inter- and intra-class similarities, class imba...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-025-02966-0

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

Deep learning and education for sustainability

Kevin Warburton • International Journal of Sustainability in Higher Education (2003)

Deep learning is a key strategy by which students extract meaning and understanding from course materials and experiences. Because of the range and interconnectedness of environmental, social and economic issues, and the importance of inter...

OPENALEX DOI: https://doi.org/10.1108/14676370310455332

The Effects of Gender Signals and Performance in Online Product Reviews

Sandipan Sikdar, Rachneet Sachdeva, Johannes Wachs, Johannes Wachs et al. • Frontiers in Big Data (2022)

This work quantifies the effects of signaling gender through gender specific user names, on the success of reviews written on the popular amazon.com shopping platform. Highly rated reviews play an important role in e-commerce since they are...

DOAJ Open Access (DOAJ) DOI: 10.3389/fdata.2021.771404