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Combining the YOLOv4 Deep Learning Model with UAV Imagery Processing Technology in the Extraction and Quantization of Cracks in Bridges

Szu-Pyng Kao, Yung-Chen Chang, Feng-Liang Wang • Sensors (2023)

Bridges are often at risk due to the effects of natural disasters, such as earthquakes and typhoons. Bridge inspection assessments normally focus on cracks. However, numerous concrete structures with cracked surfaces are highly elevated or ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23052572

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

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

Machine and deep learning methods for radiomics

Michele Avanzo, Lise Wei, Joseph Stancanello, Martin Vallières et al. • Medical Physics (2020)

Radiomics is an emerging area in quantitative image analysis that aims to relate large-scale extracted imaging information to clinical and biological endpoints. The development of quantitative imaging methods along with machine learning has...

OPENALEX other-oa DOI: https://doi.org/10.1002/mp.13678 PMC: 8965689

Teaching for Deep Learning

Tracy W. Smith, Susan A. Colby • The Clearing House A Journal of Educational Strategies Issues and Ideas (2007)

The authors have been engaged in research focused on students' depth of learning as well as teachers' efforts to foster deep learning. Findings from a study examining the teaching practices and student learning outcomes of sixtyfour teacher...

OPENALEX DOI: https://doi.org/10.3200/tchs.80.5.205-210

Computational Linguistics and Deep Learning

Christopher D. Manning • Computational Linguistics (2015)

Deep Learning waves have lapped at the shores of computational linguistics for several years now, but 2015 seems like the year when the full force of the tsunami hit the major Natural Language Processing (NLP) conferences. However, some pun...

OPENALEX Open Access DOI: https://doi.org/10.1162/coli_a_00239

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

A 2D and 3D segmentation-based microstructure study on the role of brittle phases in diffusion brazed AISI 304L/NiCrSiFeMoB joints

Johannes L. Otto, Lukas M. Sauer, Malte Brink, Thorge Schaum et al. • Materials & Design (2023)

Nickel-based filler metals are frequently used in high temperature vacuum diffusion brazing for austenitic stainless-steel joints when components are subjected to high static or dynamic loads, corrosive environments and elevated temperature...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.matdes.2023.112401

Deep Learning for Sequential Recommendation

Hui Fang, Danning Zhang, Yiheng Shu, Guibing Guo • ACM Transactions on Information Systems (2020)

In the field of sequential recommendation, deep learning--(DL) based methods have received a lot of attention in the past few years and surpassed traditional models such as Markov chain-based and factorization-based ones. However, there is ...

OPENALEX Open Access DOI: https://doi.org/10.1145/3426723

Deep Learning-Based Land Cover Extraction from Very-High-Resolution Satellite Imagery for Assisting Large-Scale Topographic Map Production

Yofri Furqani Hakim, Fuan Tsai • Remote Sensing (2025)

The demand for large-scale topographic maps in Indonesia has significantly increased due to the implementation of several government initiatives that necessitate the utilization of spatial data in development planning. Currently, the nation...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs17030473

PharmaNet Deep: Real-Time Pharmaceutical Defect Detection Using Defect-Guided Feature Fusion and Uncertainty-Driven Inspection

Ajantha Vijayakumar, Joseph Abraham Sundar Koilraj, Muthaiah Rajappa • International Journal of Computational Intelligence Systems (2025)

Abstract Oral dosage forms are the most widely employed method of drug delivery in therapeutic treatments. However, the presence of visual defects in blister packages can adversely affect the drug's bioavailability and therapeutic efficacy,...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44196-025-00986-2

Recurrent Neural Networks Based Online Behavioural Malware Detection Techniques for Cloud Infrastructure

Jeffrey C. Kimmel, Andrew D. Mcdole, Mahmoud Abdelsalam, Maanak Gupta et al. • IEEE Access (2021)

Several organizations are utilizing cloud technologies and resources to run a range of applications. These services help businesses save on hardware management, scalability and maintainability concerns of underlying infrastructure. Key clou...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3077498

Ship Detection With SAR C-Band Satellite Images: A Systematic Review

Cyprien Alexandre, Rodolphe Devillers, David Mouillot, Raphael Seguin et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024)

Detecting and tracking ships remotely is now required in a wide range of contexts, from military security to illegal immigration control, as well as the management of fisheries and marine protected areas. Among the available methods, radar ...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2024.3437187

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

Object Detection With Deep Learning: A Review

Zhong‐Qiu Zhao, Peng Zheng, Shou-Tao Xu, Xindong Wu • IEEE Transactions on Neural Networks and Learning Systems (2019)

Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable...

OPENALEX Open Access DOI: https://doi.org/10.1109/tnnls.2018.2876865

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