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Showing 20 of 762 academic articles

Credit card fraud detection in the era of disruptive technologies: A systematic review

Asma Cherif, Arwa Badhib, Heyfa Ammar, Suhair Alshehri et al. • Journal of King Saud University: Computer and Information Sciences (2023)

Credit card fraud is becoming a serious and growing problem as a result of the emergence of innovative technologies and communication methods, such as contactless payment. In this article, we present an in-depth review of cutting-edge resea...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jksuci.2022.11.008

Enhancing Deep Learning–Based Subabdominal MR Image Segmentation During Rectal Cancer Treatment: Exploiting Multiscale Feature Pyramid Network and Bidirectional Cross-Attention Mechanism

Yu Xiao, Xin Yang, Sijuan Huang, Lihua Guo • International Journal of Biomedical Imaging (2025)

Conclusion: A multiscale feature pyramid network effectively reduces the semantic gap, and the bidirectional cross-attention mechanism facilitates feature alignment between the encoding and decoding stages....

DOAJ Open Access (DOAJ) DOI: 10.1155/ijbi/7560099

A Dual-Segmentation Framework for the Automatic Detection and Size Estimation of Shrimp

Malik Muhammad Waqar, Hassan Ali, Heng Zhou, Heba G. Mohamed et al. • Sensors (2025)

In shrimp farming, determining the physical traits of shrimp is vital for assessing their health and growth. One of the critical traits is their size, as it serves as a key indicator of growth rates, biomass, and effective feed management. ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s25185830

Deep Learning-Based Prediction of the Axial Capacity of CFRP-Strengthened Concrete Columns

Nasim Shakouri Mahmoudabadi, Charles V. Camp, Afaq Ahmad • Infrastructures (2026)

Fiber-reinforced polymer (FRP) composites are widely used to strengthen reinforced concrete (RC) columns due to their high strength, durability, and ease of installation. Accurate prediction of the axial capacity of CFRP-strengthened concre...

DOAJ Open Access (DOAJ) DOI: 10.3390/infrastructures11050151

Theano: Deep Learning on GPUs with Python

James Bergstra, Frédéric Bastien, Olivier Breuleux, Pascal Lamblin et al. (2012)

In this paper, we present Theano1, a framework in the Python programming language for defining, optimizing and evaluating expressions involving high-level operations on ten-sors. Theano offers most of NumPy’s functionality, but adds automat...

OPENALEX

Deep Learning in Remote Sensing: A Comprehensive Review and List of Resources

Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia et al. • IEEE Geoscience and Remote Sensing Magazine (2017)

Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are becoming increasingly important. In particular, deep learning has proven to be both a major breakthrough and an extremely powerful tool in ...

OPENALEX Open Access DOI: https://doi.org/10.1109/mgrs.2017.2762307

A Simple Baseline for Bayesian Uncertainty in Deep Learning

Wesley J. Maddox, Timur Garipov, Pavel Izmailov, Dmitry Vetrov et al. • arXiv (Cornell University) (2019)

We propose SWA-Gaussian (SWAG), a simple, scalable, and general purpose approach for uncertainty representation and calibration in deep learning. Stochastic Weight Averaging (SWA), which computes the first moment of stochastic gradient desc...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1902.02476

Deep learning: A philosophical introduction

Cameron J. Buckner • Philosophy Compass (2019)

Abstract Deep learning is currently the most prominent and widely successful method in artificial intelligence. Despite having played an active role in earlier artificial intelligence and neural network research, philosophers have been larg...

OPENALEX DOI: https://doi.org/10.1111/phc3.12625

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

Deep learning in robotics: a review of recent research

Harry A. Pierson, Michael S. Gashler • Advanced Robotics (2017)

Advances in deep learning over the last decade have led to a flurry of research in the application of deep artificial neural networks to robotic systems, with at least 30 papers published on the subject between 2014 and the present. This re...

OPENALEX Open Access DOI: https://doi.org/10.1080/01691864.2017.1365009

Review of deep learning for photoacoustic imaging

Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao • Photoacoustics (2020)

Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.pacs.2020.100215 PMC: 7779783

Deep Learning

• De Gruyter eBooks (2020)

This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep...

OPENALEX DOI: https://doi.org/10.1515/9783110670905

Deep Learning with Applications Using Python

Navin Kumar Manaswi • Apress eBooks (2018)

This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such ...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-3516-4

Computer‐aided diagnosis in the era of deep learning

Heang‐Ping Chan, Lubomir M. Hadjiiski, Ravi K. Samala • Medical Physics (2020)

Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then ...

OPENALEX Open Access DOI: https://doi.org/10.1002/mp.13764 PMC: 7293164

Face recognition in dense crowd using deep learning approaches with IP camera

Sobhana Mummaneni, Venkata Chaitanya Satya Ramaraju Mudunuri, Sri Veerabhadra Vikas Bommaganti, Bhavya Vani Kalle et al. • Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska (2025)

A facial recognition system is a biometric security and surveillance system that can identify and monitor individuals in a crowded area. Manually monitoring a crowded environment is a difficult and error-prone task. Therefore, in such conte...

DOAJ Open Access (DOAJ) DOI: 10.35784/iapgos.6818