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Applications of deep learning to MRI images: A survey

Jin Liu, Yi Feng Pan, Min Li, Ziyue Chen et al. • Big Data Mining and Analytics (2018)

Deep learning provides exciting solutions in many fields, such as image analysis, natural language processing, and expert system, and is seen as a key method for various future applications. On account of its non-invasive and good soft tiss...

OPENALEX cc-by DOI: https://doi.org/10.26599/bdma.2018.9020001

Detection of short-term peaks in VLF/LF signals around the time of gamma-ray burst detections using deep learning

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

Predicting Parameters in Deep Learning

Misha Denil, Babak Shakibi, Laurent Dinh, Marc’Aurelio Ranzato et al. • arXiv (Cornell University) (2013)

We demonstrate that there is significant redundancy in the parameterization of several deep learning models. Given only a few weight values for each feature it is possible to accurately predict the remaining values. Moreover, we show that n...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1306.0543

Hierarchical Multimodal Sleep Staging with Optimized EEG, EOG, and PPG Features for Wearable Applications

Roberto De Fazio, Matteo Paiano, Ramiro Velazquez, Carolina Del-Valle-Soto et al. • Applied Sciences (2026)

Automatic sleep staging is fundamental for diagnosing sleep disorders and enabling long-term sleep monitoring with wearable devices. Although Deep Learning has significantly improved classification performance, balancing accuracy with compu...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16168164

ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning

Sarah Alhumoud, Asma Al Wazrah, Laila Alhussain, Lama Alrushud et al. • PeerJ Computer Science (2023)

COVID-19 has become a global pandemic that has affected not only the health sector but also economic, social, and psychological well-being. Individuals are using social media platforms to communicate their feelings and sentiments about the ...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.1507

Applications of Shaped-Charge Learning

Boris Galitsky • Entropy (2023)

It is well known that deep learning (DNN) has strong limitations due to a lack of explainability and weak defense against possible adversarial attacks. These attacks would be a concern for autonomous teams producing a state of high entropy ...

DOAJ Open Access (DOAJ) DOI: 10.3390/e25111496

Deep Learning in Microscopy Image Analysis: A Survey

Fuyong Xing, Yuanpu Xie, Hai Su, Fujun Liu et al. • IEEE Transactions on Neural Networks and Learning Systems (2017)

Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerg...

OPENALEX DOI: https://doi.org/10.1109/tnnls.2017.2766168

Fast reconstruction of SMS bSSFP myocardial perfusion images using noise map estimation network (NoiseMapNet): a head-to-head comparison with parallel imaging and iterative reconstruction

Naledi Lenah Adam, Grzegorz Kowalik, Andrew Tyler, Ronald Mooiweer et al. • Frontiers in Cardiovascular Medicine (2024)

BackgroundSimultaneous multi-slice (SMS) bSSFP imaging enables stress myocardial perfusion imaging with high spatial resolution and increased spatial coverage. Standard parallel imaging techniques (e.g., TGRAPPA) can be used for image recon...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcvm.2024.1350345

Comparison of Deep Learning Models for LAI Simulation and Interpretable Hydrothermal Coupling in the Loess Plateau

Junpo Yu, Yajun Si, Wen Zhao, Zeyu Zhou et al. • Plants (2025)

As the world’s largest loess deposit region, the Loess Plateau’s vegetation dynamics are crucial for its regional water–heat balance and ecosystem functioning. Leaf Area Index (LAI) serves as a key indicator bridging canopy architecture and...

DOAJ Open Access (DOAJ) DOI: 10.3390/plants14152391

A System for the Detection of Polyphonic Sound on a University Campus Based on CapsNet-RNN

Liyan Luo, Liujun Zhang, Mei Wang, Zhenghong Liu et al. • IEEE Access (2021)

In recent decades, surveillance and home security systems based on video analysis have been proposed for the automatic detection of abnormal situations. Nevertheless, in several real applications, it may be easier to detect a given event fr...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3123970

Comprehensive framework of machine learning and deep learning architectures with metaheuristic optimization for high-fidelity prediction of nanofluid specific heat capacity

Priya Mathur, Dheeraj Kumar, Farhan Sheth, Hammad Shaikh et al. • Scientific Reports (2025)

Abstract Accurately predicting the specific heat capacity of nanofluids is critical for optimizing their performance in engineering and industrial applications. This study explores twelve machine learning and deep learning models using conv...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-28268-z

Fault Detection in Steel Belts of Tires Using Magnetic Sensors and Different Deep Learning Models

Sercan Yalçın • Firat University Journal of Experimental and Computational Engineering (2025)

Tire failures pose significant safety risks, necessitating advanced inspection techniques. This research investigates the application of magnetic sensors and deep learning for detecting defects in steel belts of the tires. It was aim to dev...

DOAJ Open Access (DOAJ) DOI: 10.62520/fujece.1527246

Automated deep bottleneck residual 82-layered architecture with Bayesian optimization for the classification of brain and common maternal fetal ultrasound planes

Fatima Rauf, Muhammad Attique Khan, Ali Kashif Bashir, Kiran Jabeen et al. • Frontiers in Medicine (2023)

Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2023.1330218

HDLTex: Hierarchical Deep Learning for Text Classification

Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, Kiana Jafari Meimandi et al. • International Conference on Machine Learning and Applications (2017)

Increasingly large document collections require improved information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which has become an importan...

OPENALEX Open Access DOI: https://doi.org/10.1109/icmla.2017.0-134

The unreasonable effectiveness of deep learning in artificial intelligence

Terrence J. Sejnowski A B • Proceedings of the National Academy of Sciences (2020)

Deep learning networks have been trained to recognize speech, caption photographs, and translate text between languages at high levels of performance. Although applications of deep learning networks to real-world problems have become ubiqui...

OPENALEX Open Access DOI: https://doi.org/10.1073/pnas.1907373117 PMC: 7720171

A State-of-the-Art Survey on Deep Learning Theory and Architectures

Md Zahangir Alom, Tarek M. Taha, Chris Yakopcic, Stefan K.E. Westberg et al. • Electronics (2019)

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some ne...

OPENALEX cc-by DOI: https://doi.org/10.3390/electronics8030292

A comprehensive review on ensemble deep learning: Opportunities and challenges

Ammar Mohammed, Rania Kora • Journal of King Saud University - Computer and Information Sciences (2023)

In machine learning, two approaches outperform traditional algorithms: ensemble learning and deep learning. The former refers to methods that integrate multiple base models in the same framework to obtain a stronger model that outperforms t...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.jksuci.2023.01.014