Reset
Showing 20 of 2,687 academic articles

Integrating multi-source geoscience data with RF-weighted conditional variational autoencoders (CVAE) for porphyry copper prospectivity mapping: an application to the Ardestan district, Central Iran

Samane Esmaelzade Kalkhoran, Seyyed Saeed Ghannadpour • Scientific Reports (2026)

Abstract Porphyry Cu deposits in the Urmia–Dokhtar magmatic belt constitute important exploration targets, yet the heterogeneous and multi-scale nature of geological, geochemical, and remote sensing data introduces substantial uncertainty i...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-61085-6

A Comparison of Two Neural Network Based Methods for Human Activity Recognition

saeedeh zebhi, Seyed Mohammad Taghi AlModaressi, Vahid Abootalebi • AUT Journal of Electrical Engineering (2021)

In this paper, two different methods of human activity recognition based on video signals are introduced. The first method explores the effectiveness of combining feature descriptors obtained by local descriptors and artificial neural network ...

DOAJ Open Access (DOAJ) DOI: 10.22060/eej.2020.18517.5357

A deep learning-driven pipeline for differentiating hypertrophic cardiomyopathy from cardiac amyloidosis using 2D multi-view echocardiography

Xiaofeng Li, Bo Peng, Xinyu Li, Zhenghan Wang et al. • Scientific Reports (2026)

Abstract Hypertrophic Cardiomyopathy (HCM) and Cardiac Amyloidosis (CA) are two cardiac conditions that can advance to heart failure if left untreated, which present considerable diagnostic challenges due to their overlapping echocardiograp...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-15443-5

Siamese text classification network (SiamTCN) for multi-class multi-label information extraction of typhoon disasters from social media data

Zhi He, Chengle Zhou, Liwei Zou, Suhong Zhou et al. • International Journal of Digital Earth (2025)

Accurately monitoring disaster effects is a crucial task in relief efforts (e.g. typhoon rescue). Social media data plays a vital role in disaster management, while deep learning-based methods gain more attention in typhoon disaster researc...

DOAJ Open Access (DOAJ) DOI: 10.1080/17538947.2025.2517790

Deep Learning-Based Land Cover Extraction from Very-High-Resolution Satellite Imagery for Assisting Large-Scale Topographic Map Production

Yofri Furqani Hakim, Fuan Tsai • Remote Sensing (2025)

The demand for large-scale topographic maps in Indonesia has significantly increased due to the implementation of several government initiatives that necessitate the utilization of spatial data in development planning. Currently, the nation...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs17030473

Deep Learning for Computer Vision: A Brief Review

Athanasios S. Voulodimos, Nikolaos D. Doulamis, Anastasios D. Doulamis, Eftychios E. Protopapadakis • Computational Intelligence and Neuroscience (2018)

Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief ...

OPENALEX cc-by DOI: https://doi.org/10.1155/2018/7068349 PMC: 5816885

Rapid identification of bloodstream infection pathogens and drug resistance using Raman spectroscopy enhanced by convolutional neural networks

Haiquan Kang, Haiquan Kang, Ziling Wang, Jingfang Sun et al. • Frontiers in Microbiology (2024)

Bloodstream infections (BSIs) are a critical medical concern, characterized by elevated morbidity, mortality, extended hospital stays, substantial healthcare costs, and diagnostic challenges. The clinical outcomes for patients with BSI can ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmicb.2024.1428304

Development of an automated two pronuclei detection system on time‐lapse embryo images using deep learning techniques

Noritaka Fukunaga, Sho Sanami, Hiroya Kitasaka, Yuji Tsuzuki et al. • Reproductive Medicine and Biology (2020)

Abstract Purpose To establish an automated pronuclei determination system by analysis using deep learning technology which is able to effectively learn with limited amount of supervised data. Methods An algorithm was developed by explicitly...

DOAJ Open Access (DOAJ) DOI: 10.1002/rmb2.12331

The rise of deep learning in drug discovery

Hongming Chen, Ola Engkvist, Yinhai Wang, Marcus Olivecrona et al. • Drug Discovery Today (2018)

Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural networks, this technology has shown superior performance to other...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.drudis.2018.01.039

Deep learning-based MRI model for predicting P53-mutated hepatocellular carcinoma

Lulu Jia, Qing Yang, Hanchen Jiang, Gang Huang et al. • BMC Medical Imaging (2025)

Abstract Background The P53-mutated Hepatocellular Carcinoma (HCC) is an aggressive variant associated with vascular endothelial growth factor (VEGF) overexpression and increased microvascular density. This study aimed to develop an MRI-bas...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12880-025-02045-w

A Fast Inference Vision Transformer for Automatic Pavement Image Classification and Its Visual Interpretation Method

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

Advancements in 7T magnetic resonance diffusion imaging: Technological innovations and applications in neuroimaging

Lisha Nie, Siyi Li, Bing Wu, Yuhui Xiong et al. • iRADIOLOGY (2024)

Abstract The development of 7‐Tesla (7T) magnetic resonance imaging systems has opened new avenues for exploring the advantages of diffusion imaging at higher field strengths, especially in neuroscience research. This review investigates wh...

DOAJ Open Access (DOAJ) DOI: 10.1002/ird3.92

Deep learning for computational chemistry

Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu • Journal of Computational Chemistry (2017)

The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning,...

OPENALEX Open Access DOI: https://doi.org/10.1002/jcc.24764

Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery

Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn • BMC Medical Imaging (2025)

Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12880-025-01643-y

HIFU Tissue Degeneration Classification Based on Multifractal Detrending Fluctuation Analysis and Vision Transformer

Hu Dong, Xin Tong, Gang Liu • Fractal and Fractional (2026)

For high-intensity focused ultrasound (HIFU) thermal ablation to be safe and effective, real-time, high-precision monitoring of tissue coagulative necrosis is essential. However, decoding the ultra-long, non-stationary radio frequency (RF) ...

DOAJ Open Access (DOAJ) DOI: 10.3390/fractalfract10090609

The Microbiome Composition of a Man's Penis Predicts Incident Bacterial Vaginosis in His Female Sex Partner With High Accuracy

Supriya D. Mehta, Dan Zhao, Stefan J. Green, Walter Agingu et al. • Frontiers in Cellular and Infection Microbiology (2020)

Background: We determined the predictive accuracy of penile bacteria for incident BV in female sex partners. In this prospective cohort, we enrolled Kenyan men aged 18–35 and their female sex partners aged 16 and older. We assessed BV at ba...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcimb.2020.00433

Towards Neural‐Network‐Based Optical Temperature Sensing of Semiconductor Membrane External Cavity Laser

Jakob Mannstadt, Arash Rahimi‐Iman • Advanced Sensor Research (2025)

Abstract A machine‐learning (ML) non‐contact method to determine the temperature of a laser gain medium via its laser emission with a trained few‐layer neural‐network (NN) model is presented. The training of the feed‐forward NN enables the ...

DOAJ Open Access (DOAJ) DOI: 10.1002/adsr.70009