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Showing 20 of 1,964 academic articles
Wu Huiyong, Zunlong Wang • PLoS ONE
(2025)
With the increasing complexity and prosperity of global financial markets, stock market forecasting plays a critical role in investment decision-making, market regulation, and economic planning. This study proposes a hybrid prediction model...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0330324
Yao He, Jing Yang, Shaobo Li, Jianjun Hu et al. • Complex & Intelligent Systems
(2024)
Abstract Catastrophic forgetting in neural networks is a common problem, in which neural networks lose information from previous tasks after training on new tasks. Although adopting a regularization method that preferentially retains the pa...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s40747-024-01350-1
Jeffrey M. Ede • Machine Learning Science and Technology
(2020)
Abstract Deep learning is transforming most areas of science and technology, including electron microscopy. This review paper offers a practical perspective aimed at developers with limited familiarity. For context, we review popular applic...
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DOI: https://doi.org/10.1088/2632-2153/abd614
Peter R. Wiecha, Arnaud Arbouet, Christian Girard, Otto L. Muskens • Photonics Research
(2021)
Deep learning in the context of nano-photonics is mostly discussed in terms of its potential for inverse design of photonic devices or nano-structures. Many of the recent works on machine-learning inverse design are highly specific, and the...
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Open Access
DOI: https://doi.org/10.1364/prj.415960
Anindya Gupta, Philip John Harrison, Håkan Wieslander, Nicolas Pielawski et al. • Cytometry Part A
(2018)
Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and ho...
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cc-by-nc
DOI: https://doi.org/10.1002/cyto.a.23701
PMC: 6590257
Leon Herrmann, Stefan Kollmannsberger • Computational Mechanics
(2024)
Abstract The rapid growth of deep learning research, including within the field of computational mechanics, has resulted in an extensive and diverse body of literature. To help researchers identify key concepts and promising methodologies w...
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DOI: https://doi.org/10.1007/s00466-023-02434-4
Jiquan Ngiam, Adam Coates, Ahbik Lahiri, Bobby Prochnow et al. • International Conference on Machine Learning
(2011)
The predominant methodology in training deep learning advocates the use of stochastic gradient descent methods (SGDs). Despite its ease of implementation, SGDs are difficult to tune and parallelize. These problems make it challenging to dev...
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Dulani Meedeniya • Chapman & Hall/CRC eBooks
(2023)
This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising....
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public-domain
DOI: https://doi.org/10.1201/9781003390824
Hakje Yoo, Taeyong Sim • IEEE Access
(2022)
Coarse registration is the first step in determining the accuracy of surgical navigation. The purpose of this study was to present an automated coarse registration (ACR) methodology to improve the convenience and accuracy. For this purpose,...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2022.3218458
Zhenkang Wang, Nan Xia, Jiale Liang, Jiechen Wang • Geo-spatial Information Science
(2026)
China’s rapid urbanization has led to the emergence of urban villages (UVs), whose governance is crucial for urban quality and built environment management. However, conventional identification methods rely on high-resolution remote sensing...
DOAJ
Open Access (DOAJ)
DOI: 10.1080/10095020.2026.2711549
Umara Zafar, Mubeen Ghafoor, Tehseen Zia, Ghufran Ahmed et al. • EURASIP Journal on Image and Video Processing
(2019)
Abstract Recognition of facial images is one of the most challenging research issues in surveillance systems due to different problems including varying pose, expression, illumination, and resolution. The robustness of recognition method st...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13640-019-0406-y
Taikang Yuan, Junxing Zhu, Wuxin Wang, Jingze Lu et al. • Remote Sensing
(2023)
Sea surface temperature (SST) prediction has attracted increasing attention, due to its crucial role in understanding the Earth’s climate and ocean system. Existing SST prediction methods are typically based on either physics-based numerica...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs15143498
Sarnovský M., Nina A., Popović L.Č., Srećković V. et al. • Serbian Astronomical Journal
(2026)
Gamma-ray bursts (GRBs) are recognized as the most energetic and luminous astrophysical phenomena whose high-energy photons can ionize atmospheric
particles and thus affect electrical conductivity. Consequently,
electromagnetic waves ...
DOAJ
Open Access (DOAJ)
DOI: 10.2298/SAJ2612107S
Vijayamanikandan Vijayarangan, Harshavardhana A. Uranakara, Francisco E. Hernández–Pérez, Hong G. Im • Energy and AI
(2025)
Using information theory, this study provides insights into how the construction of latent space of autoencoder (AE) using deep neural network (DNN) training finds a smooth (non-stiff) low-dimensional manifold in the stiff dynamical system....
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.egyai.2025.100567
Ning Zhang, Enxu Zhang, Fei Li • Applied Sciences
(2023)
Soybean is a type of food crop with economic benefits. Whether they are damaged or not directly affects the survival and nutritional value of soybean plants. In machine learning, unbalanced data represent a major factor affecting machine le...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app13116425
Ya Zhang, Ravie Chandren Muniyandi, Faizan Qamar • Applied Sciences
(2025)
In the rapid development of the Internet of Things (IoT) and large-scale distributed networks, Intrusion Detection Systems (IDS) face significant challenges in handling complex spatiotemporal features and addressing data imbalance issues. T...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15031552
Milad Mozafari, Milad Mozafari, Mohammad Ganjtabesh, Abbas Nowzari-Dalini et al. • Frontiers in Neuroscience
(2019)
Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient. Unlike the non-spiking counterparts, most of...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fnins.2019.00625
Xiaoxiao Ma, Jia Xin Wu, Shan Xue, Jian Yu Yang et al. • IEEE Transactions on Knowledge and Data Engineering
(2021)
Anomalies are rare observations (e.g., data records or events) that deviate significantly from the others in the sample. Over the past few decades, research on anomaly mining has received increasing interests due to the implications of thes...
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Open Access
DOI: https://doi.org/10.1109/tkde.2021.3118815
P. V. Chandrika, Sandeep Kelkar • Advances in medical diagnosis, treatment, and care (AMDTC) book series
(2024)
This chapter deals with the basic understanding of the deep learning model. It starts with a view of artificial intelligence, machine learning, and deep learning. It also represents how these three concepts are related to each other. The en...
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DOI: https://doi.org/10.4018/979-8-3693-1281-0.ch001
Mohammad Mustafa Taye • Computers
(2023)
In recent years, deep learning (DL) has been the most popular computational approach in the field of machine learning (ML), achieving exceptional results on a variety of complex cognitive tasks, matching or even surpassing human performance...
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DOI: https://doi.org/10.3390/computers12050091