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Sai Sri Hemantha Konala, Srinivas Koppu • Frontiers in Medicine
(2026)
IntroductionKidney-related disorders are one of the global health concerns that require timely detection to prevent severe health complications. The use of computed tomography (CT) images for accurate classification of kidney diseases is im...
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Open Access (DOAJ)
DOI: 10.3389/fmed.2026.1893419
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...
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Open Access (DOAJ)
DOI: 10.3390/fi11120246
Hao Shi, Guo Cao, Youqiang Zhang, Zixian Ge et al. • Remote Sensing
(2022)
Deep learning (DL) has recently been a core ingredient in modern computer vision tasks, triggering a wave of revolutions in various fields. The hyperspectral image (HSI) classification task is no exception. A wide range of DL-based methods ...
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Open Access (DOAJ)
DOI: 10.3390/rs14174235
Lei Zhou, Chu Zhang, Fei Liu, Zhengjun Qiu et al. • Comprehensive Reviews in Food Science and Food Safety
(2019)
Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food sci...
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DOI: https://doi.org/10.1111/1541-4337.12492
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,...
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Open Access (DOAJ)
DOI: 10.1007/s44196-025-00986-2
Shuo Han, Bo Mo, Junwei Xu, Shizun Sun et al. • International Journal of Computational Intelligence Systems
(2024)
Abstract Infrared images of sensitive targets are difficult to obtain and cannot meet the design and training needs of target detection and tracking algorithms for mobile platforms such as aircraft. This paper proposes an image translation ...
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Open Access (DOAJ)
DOI: 10.1007/s44196-024-00674-7
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 ...
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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...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3077498
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 ...
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Open Access (DOAJ)
DOI: 10.1109/JSTARS.2024.3437187
Leander van Eekelen, Joey Spronck, Monika Looijen-Salamon, Shoko Vos et al. • Scientific Reports
(2024)
Abstract Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability...
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Open Access (DOAJ)
DOI: 10.1038/s41598-024-57067-1
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...
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Open Access (DOAJ)
DOI: 10.1186/s12911-025-02966-0
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
Chao Zuo, Jiaming Qian, Shijie Feng, Wei Yin et al. • Light Science & Applications
(2022)
With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones in manufacturing, fundamental research, and engineering applications, such as quality control, n...
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DOI: https://doi.org/10.1038/s41377-022-00714-x
PMC: 8866517
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...
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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...
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Open Access (DOAJ)
DOI: 10.1186/s12880-025-02045-w
Yihan Chen, Xingyu Gu, Zhen Liu, Jia Liang • Remote Sensing
(2022)
Traditional automatic pavement distress detection methods using convolutional neural networks (CNNs) require a great deal of time and resources for computing and are poor in terms of interpretability. Therefore, inspired by the successful a...
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Open Access (DOAJ)
DOI: 10.3390/rs14081877
Xuedan Du, Yinghao Cai, Shuo Wang, Leijie Zhang • Youth Academic Annual Conference of Chinese Association of Automation (YAC)
(2016)
In recent years, deep learning has achieved great success in many fields, such as computer vision and natural language processing. Compared to traditional machine learning methods, deep learning has a strong learning ability and can make be...
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DOI: https://doi.org/10.1109/yac.2016.7804882
Sylvain Christin, Éric Hervet, Nicolas Lecomte • Methods in Ecology and Evolution
(2019)
Abstract A lot of hype has recently been generated around deep learning, a group of artificial intelligence approaches able to break accuracy records in pattern recognition. Over the course of just a few years, deep learning revolutionized ...
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Open Access
DOI: https://doi.org/10.1111/2041-210x.13256
Gabriel Chartrand, Phillip M. Cheng, Eugene Vorontsov, Michal Drozdzal et al. • Radiographics
(2017)
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods prod...
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DOI: https://doi.org/10.1148/rg.2017170077
Emanuele Aiello, Mirko Agarla, Diego Valsesia, Paolo Napoletano et al. • IEEE Access
(2024)
Large-scale self-supervised pretraining of deep learning models is known to be critical in several fields, such as language processing, where its has led to significant breakthroughs. Indeed, it is often more impactful than architectural de...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3396990