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Yu Lyu, Xiaolin Tian • Bioengineering
(2023)
Deep learning technology has achieved breakthrough research results in the fields of medical computer vision and image processing. Generative adversarial networks (GANs) have demonstrated a capacity for image generation and expression abili...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bioengineering10091091
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
Jiantao Qiu, Chao Yu, Weiling Liu, Tianxiang Yang et al. • IEEE Access
(2021)
In recent years, reinforcement learning (RL) has been widely used to solve multi-agent navigation tasks, and a high-fidelity level for the simulator is critical to narrow the gap between simulation and real-world tasks. However, high-fideli...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3085328
Hairu Luo, Peng Jia, Anmin Zhou, Yuying Liu et al. • Applied Sciences
(2022)
In a complex network, some nodes are relatively concentrated in topological structure, thus forming a relatively independent node group, which we call a community. Usually, there are multiple communities on a network, and these communities ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app122010337
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
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
Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup et al. • Neural Networks
(2022)
Deep learning (DL) and reinforcement learning (RL) methods seem to be a part of indispensable factors to achieve human-level or super-human AI systems. On the other hand, both DL and RL have strong connections with our brain functions and w...
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DOI: https://doi.org/10.1016/j.neunet.2022.03.037
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
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
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
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...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12911-025-02966-0
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
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
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...
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Open Access
DOI: https://doi.org/10.1109/tnnls.2018.2876865
Jiasi Chen, Xukan Ran • Proceedings of the IEEE
(2019)
Deep learning is currently widely used in a variety of applications, including computer vision and natural language processing. End devices, such as smartphones and Internet-of-Things sensors, are generating data that need to be analyzed in...
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DOI: https://doi.org/10.1109/jproc.2019.2921977
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
Srigiri Krishnapriya, Yepuganti Karuna • Frontiers in Oncology
(2024)
IntroductionBrain tumors are a common disease that affects millions of people worldwide. Considering the severity of brain tumors (BT), it is important to diagnose the disease in its early stages. With advancements in the diagnostic process...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fonc.2024.1347363
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...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14081877