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Academic Articles & Research Papers
Showing 20 of 80 academic articles
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
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
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
Daniel W. Otter, Julian Richard Medina, Jugal Kumar Kalita • IEEE Transactions on Neural Networks and Learning Systems
(2020)
Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This article provides a brief introduction to the field and a quick overview of deep learni...
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Open Access
DOI: https://doi.org/10.1109/tnnls.2020.2979670
Abderrazak Khediri, Ayoub Yahiaoui, Mohamed Ridda Laouar, Yacine Belhocine • Acta Informatica Pragensia
(2024)
Blackout events in smart grids can have significant impacts on individuals, communities and businesses, as they can disrupt the power supply and cause damage to the grid. In this paper, a new proactive approach to an early warning system fo...
DOAJ
Open Access (DOAJ)
DOI: 10.18267/j.aip.246
Yasha Ektefaie, William Yuan, Deborah A. Dillon, Nancy U. Lin et al. • npj Breast Cancer
(2021)
Abstract Histopathologic evaluation of biopsy slides is a critical step in diagnosing and subtyping breast cancers. However, the connections between histology and multi-omics status have never been systematically explored or interpreted. We...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41523-021-00357-y
Konstantinos Keremis, Eleni Vrochidou, George A. Papakostas • Journal of Imaging
(2025)
The ability of deep learning models to maintain consistent performance under image transformations-termed invariances, is critical for reliable deployment across diverse computer vision applications. This study presents a comprehensive empi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/jimaging11090322
Le Yang, Dongmei Jiang, Hichem Sahli • IEEE Access
(2020)
Depression disorder has become one of the major psychological diseases endangering human health. Researcher in the affective computing community is supporting the development of reliable depression severity estimation system, from multiple ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.2970496
Toke T. Høye, Johanna Ärje, Kim Bjerge, Oskar Liset Pryds Hansen et al. • Proceedings of the National Academy of Sciences
(2021)
ABSTRACT Most animal species on Earth are insects, and recent reports suggest that their abundance is in drastic decline. Although these reports come from a wide range of insect taxa and regions, the evidence to assess the extent of the phe...
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DOI: https://doi.org/10.1073/pnas.2002545117
PMC: 7812775
Khoa Anh Tran, Olga Kondrashova, Andrew Peter Bradley, Elizabeth D. Williams et al. • Genome Medicine
(2021)
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning acr...
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DOI: https://doi.org/10.1186/s13073-021-00968-x
PMC: 8477474
Xing Su, Shan Xue, Fanzhen Liu, Jia Wu et al. • IEEE Transactions on Neural Networks and Learning Systems
(2022)
Detecting a community in a network is a matter of discerning the distinct features and connections of a group of members that are different from those in other communities. The ability to do this is of great significance in network analysis...
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Open Access
DOI: https://doi.org/10.1109/tnnls.2021.3137396
Xiaofei Yang, Yunming Ye, Xutao Li, Raymond Y.K. Lau et al. • IEEE Transactions on Geoscience and Remote Sensing
(2018)
Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem. In contrast to conventional computer vision task...
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DOI: https://doi.org/10.1109/tgrs.2018.2815613
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...
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Open Access
DOI: https://doi.org/10.1162/coli_a_00239
Gustau Camps‐Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein • Wiley eBooks
(2021)
Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only re...
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Open Access
DOI: https://doi.org/10.1002/9781119646181
Jing Liu, Xuesong Hai, Keqin Li • Future Internet
(2023)
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/fi16010006
Bryan Y. Lim, Stefan Zohren • Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
(2021)
Numerous deep learning architectures have been developed to accommodate the diversity of time-series datasets across different domains. In this article, we survey common encoder and decoder designs used in both one-step-ahead and multi-hori...
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Open Access
DOI: https://doi.org/10.1098/rsta.2020.0209
Theodore Spaide, PhD, Anand E. Rajesh, MD, Nayoon Gim, Marian Blazes, MD et al. • Ophthalmology Science
(2025)
Purpose: To apply methods for quantifying uncertainty of deep learning segmentation of geographic atrophy (GA). Design: Retrospective analysis of OCT images and model comparison. Participants: One hundred twenty-six eyes from 87 participant...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.xops.2024.100587
Sergey Plis, Devon Hjelm, Ruslan Salakhutdinov, Elena A. Allen et al. • Frontiers in Neuroscience
(2014)
Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neu...
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DOI: https://doi.org/10.3389/fnins.2014.00229
PMC: 4138493