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Showing 20 of 675 academic articles
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
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
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
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
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
Fangzhou Liu, Yang Zhao, Jiqiao Chen, Ting Luo • EAI Endorsed Transactions on Energy Web
(2026)
Power distribution network fault handling imposes stringent requirements on both response timeliness and decision reliability. The high penetration of distributed renewable generation, the widespread deployment of power-electronic devices, ...
DOAJ
Open Access (DOAJ)
DOI: 10.4108/ew.13683
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
Yuwei Yin, Zhixian Tang, Huachun Weng • BioMedical Engineering OnLine
(2024)
Abstract Deep Self-Attention Network (Transformer) is an encoder–decoder architectural model that excels in establishing long-distance dependencies and is first applied in natural language processing. Due to its complementary nature with th...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12938-024-01209-z
Shiyao Duan, Jiaojiao Li, Rui Song, Yunsong Li et al. • Remote Sensing
(2023)
Deep learning networks based on CNNs or transformers have made progress in spectral reconstruction (SR). However, many methods focus solely on feature extraction, overlooking the interpretability of network design. Additionally, models excl...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs15102619
Shiv Singh, Neelu Jyothi Ahuja • Discover Computing
(2026)
Abstract The application of deep learning models in resource-constrained environments requires a trade-off among accuracy, efficiency, and interpretability a trilemma frequently neglected in conventional knowledge distillation (KD) approach...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s10791-026-10123-y
Wenqiang Liu, Li Yan, Ningning Ma, Gaozhou Wang et al. • Applied Sciences
(2024)
With the rapid development of deep learning, researchers are actively exploring its applications in the field of industrial anomaly detection. Deep learning methods differ significantly from traditional mathematical modeling approaches, eli...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app14020774
Hao Xing, Guigang Zhang, Shang Ma • International Journal of Semantic Computing
(2016)
Deep learning is a branch of machine learning that tries to model high-level abstractions of data using multiple layers of neurons consisting of complex structures or non-liner transformations. With the increase of the amount of data and th...
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DOI: https://doi.org/10.1142/s1793351x16500045
Khalil A. Alruwaitee • Journal of Radiation Research and Applied Sciences
(2024)
Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrras.2024.101172
Sina Ardabili, Amir Hosein Mosavi, Pedram Ghamisi, Ferdinánd Filip et al. • Algorithms
(2020)
Abstract Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simpl...
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DOI: https://doi.org/10.3390/a13100249
Grace W. Lindsay • Frontiers in Computational Neuroscience
(2020)
Attention is the important ability to flexibly control limited computational resources. It has been studied in conjunction with many other topics in neuroscience and psychology including awareness, vigilance, saliency, executive control, an...
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DOI: https://doi.org/10.3389/fncom.2020.00029
PMC: 7177153
Ming Han, Ge Sun, Paul F. Nealey, Juan J. de Pablo • npj Computational Materials
(2025)
Abstract Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41524-025-01836-7
Paolo Graniero, Paolo Graniero, Mark Khenkin, Hans Köbler et al. • Frontiers in Energy Research
(2023)
Perovskite solar cells are the most dynamic emerging photovoltaic technology and attracts the attention of thousands of researchers worldwide. Recently, many of them are targeting device stability issues–the key challenge for this technolog...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fenrg.2023.1118654
Zetao Yan • Egyptian Informatics Journal
(2025)
Portfolio optimization is a process that involves distribution of capital with the purpose of maximizing returns and at the same time minimizing risks. The current paper discusses the use of Transformer networks in supervised learning for p...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.eij.2025.100839
Guang Liu, Xiaojie Wang • IEEE Access
(2019)
Stock market prediction is of great importance for financial analysis. Traditionally, many studies only use the news or numerical data for the stock market prediction. In the recent years, in order to explore their complementary, some studi...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2018.2886367
Juan Carrasquilla • Advances in Physics X
(2020)
Quantum matter, the research field studying phases of matter whose properties are intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter physics, materials science, statistical mechanics, quantum information,...
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DOI: https://doi.org/10.1080/23746149.2020.1797528