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Academic Articles & Research Papers
Showing 20 of 100 academic articles
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
Justin M. Johnson, Taghi M. Khoshgoftaar • Journal Of Big Data
(2019)
The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective classification with imbalanced data is an important area of research, as high class imbalance is naturally inherent in...
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DOI: https://doi.org/10.1186/s40537-019-0192-5
Gabriel Chartrand, Phillip M. Cheng, Eugene Vorontsov, Michal Drozdzal et al. • Radiographics
(2017)
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods prod...
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DOI: https://doi.org/10.1148/rg.2017170077
Ko-Tsung Hsu, Steven Guan, Parag V. Chitnis • Photoacoustics
(2023)
Iterative reconstruction has demonstrated superior performance in medical imaging under compressed, sparse, and limited-view sensing scenarios. However, iterative reconstruction algorithms are slow to converge and rely heavily on hand-craft...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.pacs.2023.100452
Samira Pouyanfar, Saad B Sadiq, Yilin Yan, Haiman Tian et al. • ACM Computing Surveys
(2018)
The field of machine learning is witnessing its golden era as deep learning slowly becomes the leader in this domain. Deep learning uses multiple layers to represent the abstractions of data to build computational models. Some key enabler d...
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DOI: https://doi.org/10.1145/3234150
Seonwoo Min, Byunghan Lee, Sungroh Yoon • Briefings in Bioinformatics
(2016)
In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-th...
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Open Access
DOI: https://doi.org/10.1093/bib/bbw068
Clara Muñoz-Castro, Ayush Noori, Colin G. Magdamo, Zhaozhi Li et al. • Journal of Neuroinflammation
(2022)
Abstract Background Astrocytes and microglia react to Aβ plaques, neurofibrillary tangles, and neurodegeneration in the Alzheimer’s disease (AD) brain. Single-nuclei and single-cell RNA-seq have revealed multiple states or subpopulations of...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12974-022-02383-4
Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing
(2018)
Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs10071119
Xuan V. Nguyen, Devi D. Nelakurti, Engin Dikici, Sema Candemir et al. • Information
(2022)
Background: Distinguishing between the spinal cord and cerebrospinal fluid (CSF) non-invasively on CT is challenging due to their similar mass densities. We hypothesize that patch-based machine learning applied to dual-energy CT can accurat...
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Open Access (DOAJ)
DOI: 10.3390/info13090412
Galen Richardson, Sylvain G. Leblanc, Julie Lovitt, Krishan Rajaratnam et al. • Drones
(2021)
Relating ground photographs to UAV orthomosaics is a key linkage required for accurate multi-scaled lichen mapping. Conventional methods of multi-scaled lichen mapping, such as random forest models and convolutional neural networks, heavily...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/drones5030099
Ł. Wilk, Ł. Wilk, D. Mielczarek, W. Ostrowski et al. • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
(2022)
The use of deep machine learning methods for semantic classification of city mesh models is one of the current trends in geoscience development. Thanks to the thriving development of Convolutional Neural Networks (CNNs) it is now achievable...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/isprs-archives-XLIII-B2-2022-485-2022
Zeynep Akkutay-Yoldar, Mehmet Türkay Yoldar, Yiğit Burak Akkaş, Sibel Şurak et al. • Scientific Reports
(2025)
Abstract Identifying viral replication within cells demands labor-intensive isolation methods, requiring specialized personnel and additional confirmatory tests. To facilitate this process, we developed an AI-powered automated system called...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-89639-0
Hao Xu, Yuntian Chen, Dongxiao Zhang • Advanced Science
(2022)
Abstract The interpretability of deep neural networks has attracted increasing attention in recent years, and several methods have been created to interpret the “black box” model. Fundamental limitations remain, however, that impede the pac...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/advs.202204723
Jiayun Xin, Mohammad Khishe, Diyar Qader Zeebaree, Laith Abualigah et al. • Heliyon
(2024)
Deep Convolutional Neural Networks (DCNNs) have shown remarkable success in image classification tasks, but optimizing their hyperparameters can be challenging due to their complex structure. This paper develops the Adaptive Habitat Biogeog...
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Open Access (DOAJ)
DOI: 10.1016/j.heliyon.2024.e28147
Muhammad Irfan, Zohaib Mushtaq, Nabeel Ahmed Khan, Salim Nasar Faraj Mursal et al. • IEEE Access
(2023)
Machine learning (ML) based bearing fault detection is an emerging application of Artificial Intelligence (AI) that has proven its utility in effectively classifying various faults for timely measures. There are myriad studies dedicated to ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3332243
J.E. Soun, D.S. Chow, M. Nagamine, R.S. Takhtawala et al. • American Journal of Neuroradiology
(2020)
Artificial intelligence technology is a rapidly expanding field with many applications in acute stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute stroke is critical for initiating prompt intervention ...
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DOI: https://doi.org/10.3174/ajnr.a6883
PMC: 7814792
Kecheng Huang, Chujun Wu, Rongpeng Pi, Jieyu Fang • JMIR Medical Informatics
(2025)
This viewpoint article explores the transformative role of artificial intelligence (AI) in predicting perioperative hypoxemia through the integration of deep learning with multimodal clinical data, including lung imaging, pulmonary function...
DOAJ
Open Access (DOAJ)
DOI: 10.2196/73995
Nodir Rakhimov, Jura Kuvandikov, Ma'ruf Tojiyev, Dilmurod Khasanov et al. • Frontiers in Artificial Intelligence
(2026)
Unmanned aerial vehicle imagery provides a practical and high-resolution data source for monitoring the spatial condition of urban and peri-urban green zones. However, the reliable detection of damaged, stressed, or declining vegetation are...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/frai.2026.1910842
Lijo Jacob Varghese, Suma Sira Jacob, Jaisiva Selvaraj, Tefera Mekonnen Azerefegn • Scientific Reports
(2025)
Abstract This article describes a method for improving power grid voltage profiles by more effectively regulating reactive power through the integration of hybrid renewable energy systems (HRES) in smart grids. The unpredictable nature of r...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-24751-9
Ursula Margarethe Schmidt-Erfurth, Amir Sadeghipour, Bianca S. Gerendas, Sebastian M. Waldstein et al. • Progress in Retinal and Eye Research
(2018)
Major advances in diagnostic technologies are offering unprecedented insight into the condition of the retina and beyond ocular disease. Digital images providing millions of morphological datasets can fast and non-invasively be analyzed in ...
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DOI: https://doi.org/10.1016/j.preteyeres.2018.07.004