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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

Heart Disease Detection using ML and ES (Smart Wearable Health Monitoring System)

Marwan Aly, Mostafa Kamal, Mahmoud Ossman, Kamel El-Sehly et al. • Kafrelsheikh Journal of Information Sciences (2021)

This paper proposed a smart wearable system for heart disease detection using machine learning and embedded systems. A smart wearable system that able to monitor the heart beat rate condition of patient. The heart beat rate is detected usin...

DOAJ Open Access (DOAJ) DOI: 10.21608/kjis.2021.42695.1009

DVNDTA: a dual virtual node based heterogeneous interaction model for accurate prediction of drug-target affinity

Guoqiang Zhou, Ben Li, Weifeng Zhang, Shudi Bao et al. • BMC Bioinformatics (2026)

Abstract Efficient prediction of drug-target affinity (DTA) is crucial for accelerating drug discovery. Recently, deep learning approaches leveraging 3D complexes have shown strong potential for drug-target affinity prediction. However, mos...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12859-026-06481-5

A Review on Conventional Machine Learning vs Deep Learning

Nitin Kumar Chauhan, Krishna Pal Singh • International Conference on Computing, Power and Communication Technologies (GUCON) (2018)

In now days, deep learning has become a prominent and emerging research area in computer vision applications. Deep learning permits the multiple layers models for computation to learn representations of data by processing in their original ...

OPENALEX DOI: https://doi.org/10.1109/gucon.2018.8675097

Deep learning in medical imaging and radiation therapy

Berkman Sahiner, Aria X. Pezeshk, Lubomir M. Hadjiiski, Xiaosong Wang et al. • Medical Physics (2018)

The goals of this review paper on deep learning (DL) in medical imaging and radiation therapy are to (a) summarize what has been achieved to date; (b) identify common and unique challenges, and strategies that researchers have taken to addr...

OPENALEX Open Access DOI: https://doi.org/10.1002/mp.13264 PMC: 9560030

Deep learning in holography and coherent imaging

Yair Rivenson, Yichen Wu, Aydogan Özcan • Light Science & Applications (2019)

Recent advances in deep learning have given rise to a new paradigm of holographic image reconstruction and phase recovery techniques with real-time performance. Through data-driven approaches, these emerging techniques have overcome some of...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41377-019-0196-0 PMC: 6804620

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

Deep learning applications in ophthalmology

Ehsan Rahimy • Current Opinion in Ophthalmology (2018)

PURPOSE OF REVIEW: To describe the emerging applications of deep learning in ophthalmology. RECENT FINDINGS: Recent studies have shown that various deep learning models are capable of detecting and diagnosing various diseases afflicting the...

OPENALEX DOI: https://doi.org/10.1097/icu.0000000000000470

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

Review: Deep Learning on 3D Point Clouds

Saifullahi Aminu Bello, Shangshu Yu, Cheng Wang, Jibril Muhammad Adam et al. • Remote Sensing (2020)

A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisi...

OPENALEX cc-by DOI: https://doi.org/10.3390/rs12111729

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