Home »
Academic Articles & Research Papers
Showing 20 of 785 academic articles
Aziz Siyaev, Geun-Sik Jo • IEEE Access
(2021)
In the emerging world of metaverses, it is essential for speech communication systems to be aware of context to interact with virtual assets in the 3D world. This paper proposes the metaverse for aircraft maintenance training and education ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3128616
Shuaifeng Li, Heng Wang, Cong Zhang, Jie Liu • IEEE Access
(2022)
To address the problem that existing deep learning methods are not sufficiently accurate to detect rice pests with changeable shapes or similar appearances, a self-attention feature fusion model for rice pest detection (SAFFPest) was propos...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2022.3194925
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
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
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
Gaurav Menghani • ACM Computing Surveys
(2023)
Deep learning has revolutionized the fields of computer vision, natural language understanding, speech recognition, information retrieval, and more. However, with the progressive improvements in deep learning models, their number of paramet...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3578938
Christopher Ardohain, Songlin Fei • Science of Remote Sensing
(2025)
Deep learning (DL) is ubiquitous in remote sensing analysis with continued evolution in model architectures and advancement of model types. However, DL is still constrained by the need for extensive training datasets, which are costly and t...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.srs.2024.100185
Xiaozheng Li, Huazhen Wang, Huixin He, Jixiang Du et al. • BMC Bioinformatics
(2019)
Abstract Background Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural n...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12859-019-2617-8
Hao Wang, Xuan Wang, Yusheng Du, You Wang et al. • European Journal of Radiology Open
(2025)
Objectives: This study aimed to develop a predictive model for lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) patients by deep learning radiomic (DLRad) and clinical features. Methods: This study included 271 thyroid lobes...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.ejro.2025.100639
Chayakrit Krittanawong, Kipp W. Johnson, Robert S. Rosenson, Zhen Wang et al. • European Heart Journal
(2019)
Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via...
OPENALEX
Open Access
DOI: https://doi.org/10.1093/eurheartj/ehz056
PMC: 6600129
Chao-Kai Wen, Wan-Ting Shih, Shi Jin • IEEE Wireless Communications Letters
(2018)
In frequency division duplex mode, the downlink channel state information (CSI) should be sent to the base station through feedback links so that the potential gains of a massive multiple-input multiple-output can be exhibited. However, suc...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/lwc.2018.2818160
June‐Goo Lee, Sanghoon Jun, Young-Won Cho, Hyunna Lee et al. • Korean Journal of Radiology
(2017)
The artificial neural network (ANN)-a machine learning technique inspired by the human neuronal synapse system-was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishin...
OPENALEX
cc-by-nc
DOI: https://doi.org/10.3348/kjr.2017.18.4.570
PMC: 5447633
Yanming Yang, Xin Xia, David Lo, John Grundy • ACM Computing Surveys
(2021)
In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)” and an improved model training method to break the bottleneck of neural network development. More recently, the introduction of AlphaGo in 2016 demonstr...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3505243
Zhonghua Feng, Minglun Ren • Applied Sciences
(2026)
Rotating machinery prognostics is essential for ensuring the reliability and operational safety of industrial systems. Although gated recurrent units (GRUs) have achieved competitive performance in remaining useful life (RUL) prediction, wh...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app16178379
Jishi Zheng, Junhui Li, Zhigang Ding, Linghua Kong et al. • Connection Science
(2023)
To prevent products with missing character information from reaching the market, manufacturers need an automatic character recognition method. One of the key problems of this recognition method is to recognise text under complex package pat...
DOAJ
Open Access (DOAJ)
DOI: 10.1080/09540091.2023.2202363
Guangyu Zhu, Xueqi Luo, Tingting Yang, Li Cai et al. • Frontiers in Physiology
(2022)
The manual identification and segmentation of intracranial aneurysms (IAs) involved in the 3D reconstruction procedure are labor-intensive and prone to human errors. To meet the demands for routine clinical management and large cohort studi...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fphys.2022.1084202
Andrew J. Reader, Guillaume Corda-D’Incan, Abolfazl Mehranian, Casper O. da Costa-Luis et al. • IEEE Transactions on Radiation and Plasma Medical Sciences
(2020)
This article reviews the use of a subdiscipline of artificial intelligence (AI), deep learning, for the reconstruction of images in positron emission tomography (PET). Deep learning can be used either directly or as a component of conventio...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/trpms.2020.3014786
Toke T. Høye, Johanna Ärje, Kim Bjerge, Oskar Liset Pryds Hansen et al. • Proceedings of the National Academy of Sciences
(2021)
ABSTRACT Most animal species on Earth are insects, and recent reports suggest that their abundance is in drastic decline. Although these reports come from a wide range of insect taxa and regions, the evidence to assess the extent of the phe...
OPENALEX
cc-by
DOI: https://doi.org/10.1073/pnas.2002545117
PMC: 7812775
Yair Rivenson, Zoltán S. Göröcs, Harun Günaydın, Yibo Zhang et al. • Optica
(2017)
We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired ...
OPENALEX
Open Access
DOI: https://doi.org/10.1364/optica.4.001437
Phillip M. Cheng, Emmanuel Montagnon, Rikiya Yamashita, Ian Pan et al. • Radiographics
(2021)
Deep learning is a class of machine learning methods that has been successful in computer vision. Unlike traditional machine learning methods that require hand-engineered feature extraction from input images, deep learning methods learn the...
OPENALEX
cc-by
DOI: https://doi.org/10.1148/rg.2021200210