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Academic Articles & Research Papers
Showing 20 of 2,610 academic articles
Saleh Albahli • Future Internet
(2019)
Since the introduction of just-in-time effort aware defect prediction, many researchers are focusing on evaluating the different learning methods, which can predict the defect inducing changes in a software product. In order to predict thes...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/fi11120246
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
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
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
Travers H. Ching, Daniel Scott Himmelstein, Brett K. Beaulieu‐Jones, Alexandr A. Kalinin et al. • Journal of The Royal Society Interface
(2018)
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and m...
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DOI: https://doi.org/10.1098/rsif.2017.0387
PMC: 5938574
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
RenHui Wu, MengMeng Yang, TianChi Wu, RongZhen Li et al. • PeerJ
(2026)
Background In recent years, skin health has garnered widespread attention, with hyperpigmentation disorders caused by excessive melanin deposition emerging as a particularly prominent concern. Tyrosinase, as the rate-limiting enzyme in the ...
DOAJ
Open Access (DOAJ)
DOI: 10.7717/peerj.20845
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
Bo Wen, Wen‐Feng Zeng, Yuxing Liao, Zhiao Shi et al. • PROTEOMICS
(2020)
Proteomics, the study of all the proteins in biological systems, is becoming a data-rich science. Protein sequences and structures are comprehensively catalogued in online databases. With recent advancements in tandem mass spectrometry (MS)...
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DOI: https://doi.org/10.1002/pmic.201900335
PMC: 7757195
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
Ajay Shrestha, Ausif Mahmood • IEEE Access
(2019)
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars, predictive forecasting, and speech recognition. The pain...
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Open Access
DOI: https://doi.org/10.1109/access.2019.2912200
Chensi Cao, Feng Liu, Hai Tan, Deshou Song et al. • Genomics Proteomics & Bioinformatics
(2018)
Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitat...
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DOI: https://doi.org/10.1016/j.gpb.2017.07.003
PMC: 6000200
Hideyuki Ogura, Masaaki Ikehara • IEEE Access
(2025)
Image colorization is a fundamental task in computer vision that aims to predict the missing color channels from grayscale images. In recent years, fully automatic approaches based on deep learning have become the dominant paradigm. However...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3646876
Md Mijanur Rahman, Ashik Uzzaman, Sadia Islam Sami, Fatema Khatun et al. • IET Image Processing
(2024)
Abstract This study introduces a novel encoder–decoder framework based on deep neural networks and provides a thorough investigation into the field of automatic picture captioning systems. The suggested model uses a “long short‐term memory”...
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Open Access (DOAJ)
DOI: 10.1049/ipr2.13287
Paschalis Bizopoulos, Dimitris Koutsouris • IEEE Reviews in Biomedical Engineering
(2018)
The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data....
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Open Access
DOI: https://doi.org/10.1109/rbme.2018.2885714
Hongming Chen, Ola Engkvist, Yinhai Wang, Marcus Olivecrona et al. • Drug Discovery Today
(2018)
Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural networks, this technology has shown superior performance to other...
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DOI: https://doi.org/10.1016/j.drudis.2018.01.039
Erik Gawehn, Jan A. Hiss, Gisbert Schneider • Molecular Informatics
(2015)
Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical ...
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DOI: https://doi.org/10.1002/minf.201501008
Khawja Imran Masud, Md Yasin Zihad, Mehedi Hasan Shuvo, Mst Raonik Jannat et al. • PLoS ONE
(2026)
Early and real-time detection of rice leaf diseases (RLD) poses a significant challenge for farmers, especially in rural regions with limited access to advanced technology. Conventional deep learning models often require substantial computa...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0356383
Lulu Jia, Qing Yang, Hanchen Jiang, Gang Huang et al. • BMC Medical Imaging
(2025)
Abstract Background The P53-mutated Hepatocellular Carcinoma (HCC) is an aggressive variant associated with vascular endothelial growth factor (VEGF) overexpression and increased microvascular density. This study aimed to develop an MRI-bas...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12880-025-02045-w
Lei Zhang, Shuai Wang, Bing Liu • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
(2018)
Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state‐of‐the‐art prediction results. Along with the success of deep learning in many appl...
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Open Access
DOI: https://doi.org/10.1002/widm.1253