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Priya Mathur, Dheeraj Kumar, Farhan Sheth, Hammad Shaikh et al. • Scientific Reports
(2025)
Abstract Accurately predicting the specific heat capacity of nanofluids is critical for optimizing their performance in engineering and industrial applications. This study explores twelve machine learning and deep learning models using conv...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-28268-z
Da Yuan, Dong Huang, Yu Lei, Minhao Wang et al. • Applied Sciences
(2026)
The penetration rate (PR) is a critical indicator affecting the safety and cost of shield tunnel construction. However, due to the complexity of geological conditions and the nonlinear nature of tunneling parameters, traditional prediction ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app16115549
Yanhui Xi, Weijie Zhang, Feng Zhou, Xin Tang et al. • Energy Reports
(2023)
Accurate fault detection and classification help to analyze fault causes and quickly restore faulty phases. Deep learning can automatically extract fault features and identify fault types from the original three-phase voltage and current si...
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Open Access (DOAJ)
DOI: 10.1016/j.egyr.2022.12.043
Sercan Yalçın • Firat University Journal of Experimental and Computational Engineering
(2025)
Tire failures pose significant safety risks, necessitating advanced inspection techniques. This research investigates the application of magnetic sensors and deep learning for detecting defects in steel belts of the tires. It was aim to dev...
DOAJ
Open Access (DOAJ)
DOI: 10.62520/fujece.1527246
Guoqiang Zhou, Ben Li, Weifeng Zhang, Shudi Bao et al. • BMC Bioinformatics
(2026)
Abstract Efficient prediction of drug-target affinity (DTA) is crucial for accelerating drug discovery. Recently, deep learning approaches leveraging 3D complexes have shown strong potential for drug-target affinity prediction. However, mos...
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Open Access (DOAJ)
DOI: 10.1186/s12859-026-06481-5
Nitin Kumar Chauhan, Krishna Pal Singh • International Conference on Computing, Power and Communication Technologies (GUCON)
(2018)
In now days, deep learning has become a prominent and emerging research area in computer vision applications. Deep learning permits the multiple layers models for computation to learn representations of data by processing in their original ...
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DOI: https://doi.org/10.1109/gucon.2018.8675097
Ehsan Rahimy • Current Opinion in Ophthalmology
(2018)
PURPOSE OF REVIEW: To describe the emerging applications of deep learning in ophthalmology. RECENT FINDINGS: Recent studies have shown that various deep learning models are capable of detecting and diagnosing various diseases afflicting the...
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DOI: https://doi.org/10.1097/icu.0000000000000470
Md Zahangir Alom, Tarek M. Taha, Chris Yakopcic, Stefan K.E. Westberg et al. • Electronics
(2019)
In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some ne...
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DOI: https://doi.org/10.3390/electronics8030292
Gaurav Menghani • ACM Computing Surveys
(2023)
Deep learning has revolutionized the fields of computer vision, natural language understanding, speech recognition, information retrieval, and more. However, with the progressive improvements in deep learning models, their number of paramet...
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Open Access
DOI: https://doi.org/10.1145/3578938
Saifullahi Aminu Bello, Shangshu Yu, Cheng Wang, Jibril Muhammad Adam et al. • Remote Sensing
(2020)
A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisi...
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DOI: https://doi.org/10.3390/rs12111729
Wan Zhu, Longxiang Xie, Jianye Han, Xiangqian Guo • Cancers
(2020)
Deep learning has been applied to many areas in health care, including imaging diagnosis, digital pathology, prediction of hospital admission, drug design, classification of cancer and stromal cells, doctor assistance, etc. Cancer prognosis...
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DOI: https://doi.org/10.3390/cancers12030603
PMC: 7139576
Ammar Mohammed, Rania Kora • Journal of King Saud University - Computer and Information Sciences
(2023)
In machine learning, two approaches outperform traditional algorithms: ensemble learning and deep learning. The former refers to methods that integrate multiple base models in the same framework to obtain a stronger model that outperforms t...
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DOI: https://doi.org/10.1016/j.jksuci.2023.01.014
Xinhang Zhang, Zhenhua Ma, Yaru Zhang, Huiying Ru • IEEE Access
(2025)
The recognition of oracle bone script is of significant importance for understanding the evolution of Chinese characters, their morphological features, and semantic changes. However, traditional methods and some deep learning models have li...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3536553
Zhihao Chen, Jie Gao, Weikai Wang, Zheng Yan • Environmental Research Letters
(2021)
The troposphere is one of the atmospheric layers where most weather phenomena occur. Temperature variations in the troposphere, especially at 500 hPa, a typical level of the middle troposphere, are significant indicators of future weather c...
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Open Access (DOAJ)
DOI: 10.1088/1748-9326/abfde9
Christopher Ardohain, Songlin Fei • Science of Remote Sensing
(2025)
Deep learning (DL) is ubiquitous in remote sensing analysis with continued evolution in model architectures and advancement of model types. However, DL is still constrained by the need for extensive training datasets, which are costly and t...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.srs.2024.100185
SUN Xuechao, ZHANG Youyuan, ZHU Jinxiang, WANG Ping et al. • Renmin Zhujiang
(2025)
Broken wire electromagnetic detection technology for prestressed concrete cylinder pipes (PCCPs) is an important technical means to maintain the safety of PCCP engineering. Although electromagnetic detection technology has a high detection ...
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Open Access (DOAJ)
Xiaozheng Li, Huazhen Wang, Huixin He, Jixiang Du et al. • BMC Bioinformatics
(2019)
Abstract Background Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural n...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12859-019-2617-8
Hao Wang, Xuan Wang, Yusheng Du, You Wang et al. • European Journal of Radiology Open
(2025)
Objectives: This study aimed to develop a predictive model for lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) patients by deep learning radiomic (DLRad) and clinical features. Methods: This study included 271 thyroid lobes...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.ejro.2025.100639
Li Deng • APSIPA Transactions on Signal and Information Processing
(2014)
In this invited paper, my overview material on the same topic as presented in the plenary overview session of APSIPA-2011 and the tutorial material presented in the same conference [1] are expanded and updated to include more recent develop...
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DOI: https://doi.org/10.1017/atsip.2013.9
Chayakrit Krittanawong, Kipp W. Johnson, Robert S. Rosenson, Zhen Wang et al. • European Heart Journal
(2019)
Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via...
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Open Access
DOI: https://doi.org/10.1093/eurheartj/ehz056
PMC: 6600129