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Nir Shlezinger, Yonina C. Eldar, Stephen Boyd • IEEE Access
(2022)
Decision making algorithms are used in a multitude of different applications. Conventional approaches for designing decision algorithms employ principled and simplified modelling, based on which one can determine decisions via tractable opt...
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DOI: https://doi.org/10.1109/access.2022.3218802
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...
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Open Access
DOI: https://doi.org/10.1145/3505243
Daniel W. Otter, Julian Richard Medina, Jugal Kumar Kalita • IEEE Transactions on Neural Networks and Learning Systems
(2020)
Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This article provides a brief introduction to the field and a quick overview of deep learni...
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Open Access
DOI: https://doi.org/10.1109/tnnls.2020.2979670
Abderrazak Khediri, Ayoub Yahiaoui, Mohamed Ridda Laouar, Yacine Belhocine • Acta Informatica Pragensia
(2024)
Blackout events in smart grids can have significant impacts on individuals, communities and businesses, as they can disrupt the power supply and cause damage to the grid. In this paper, a new proactive approach to an early warning system fo...
DOAJ
Open Access (DOAJ)
DOI: 10.18267/j.aip.246
Liyue Wu, Qinchuan Zhan, Yanjun Li • Humanities & Social Sciences Communications
(2026)
Abstract This study applies a multimodal deep learning approach to examine tourist engagement with traditional architectural heritage. The Gao Family Compound in Xi’an serves as a representative case. Social-media texts and images from Weib...
DOAJ
Open Access (DOAJ)
DOI: 10.1057/s41599-026-07879-5
Yasha Ektefaie, William Yuan, Deborah A. Dillon, Nancy U. Lin et al. • npj Breast Cancer
(2021)
Abstract Histopathologic evaluation of biopsy slides is a critical step in diagnosing and subtyping breast cancers. However, the connections between histology and multi-omics status have never been systematically explored or interpreted. We...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41523-021-00357-y
Lisi Zhang, Qiancheng Yu, Beijing Zhou, Yifan Zhang et al. • IEEE Access
(2023)
The efficacy of credit risk assessment models is pivotal to the risk management capacity of financial institutions. Traditional credit risk models often suffer from inadequate predictive accuracy due to overlooked feature combinations and w...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3322429
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
Konstantinos Keremis, Eleni Vrochidou, George A. Papakostas • Journal of Imaging
(2025)
The ability of deep learning models to maintain consistent performance under image transformations-termed invariances, is critical for reliable deployment across diverse computer vision applications. This study presents a comprehensive empi...
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Open Access (DOAJ)
DOI: 10.3390/jimaging11090322
Le Yang, Dongmei Jiang, Hichem Sahli • IEEE Access
(2020)
Depression disorder has become one of the major psychological diseases endangering human health. Researcher in the affective computing community is supporting the development of reliable depression severity estimation system, from multiple ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.2970496
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...
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Open Access
DOI: https://doi.org/10.1109/trpms.2020.3014786
Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam et al. (2011)
Deep networks have been successfully applied to unsupervised feature learning for single modalities (e.g., text, images or audio). In this work, we propose a novel application of deep networks to learn features over multiple modalities. We ...
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Licheng Jiao, Fan Zhang, Fang Liu, Shuyuan Yang et al. • IEEE Access
(2019)
Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in people’s life, such as monitoring security, autonomous driving and so on, with the purpose of locating instances of ...
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DOI: https://doi.org/10.1109/access.2019.2939201
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...
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DOI: https://doi.org/10.1073/pnas.2002545117
PMC: 7812775
Fenglei Li, Qiaoyu Hu, Xianglei Zhang, Renhong Sun et al. • Nature Communications
(2022)
The rational design of PROTACs is difficult due to their obscure structure-activity relationship. Here the authors present a deep neural network model - DeepPROTACs - for predicting the degradation capacity of a proposed PROTAC molecule....
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41467-022-34807-3
Yuying Zhang, Fei Xu, Yi Yang • Applied Sciences
(2025)
In recent years, gaze estimation has received a lot of interest in areas including human–computer interface, virtual reality, and user engagement analysis. Despite significant advances in convolutional neural network (CNN) techniques, direc...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app152312475
Zijian Wang, Haimei Lu, Haixin Yan, Hongxing Kan et al. • Scientific Reports
(2023)
Abstract Diabetic Retinopathy (DR) is a major cause of blindness worldwide. Early detection and treatment are crucial to prevent vision loss, making accurate and timely diagnosis critical. Deep learning technology has shown promise in the a...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-023-38320-5
LIU Zhaoyang, PAN Bitao • Guangtongxin yanjiu
(2024)
【Objective】Recent research efforts on Routing and Wavelength Assignment (RWA) for all optical networks are focused on Deep Reinforcement Learning (DRL) based algorithms. The DRL based RWA algorithms are mostly rely on the K Shortest Paths (...
DOAJ
Open Access (DOAJ)
Xiaojiao Chen, Xiuqing Zhang, Mi Dong, Liansheng Huang et al. • Frontiers in Energy Research
(2021)
The prediction of wind power plays an indispensable role in maintaining the stability of the entire power grid. In this paper, a deep learning approach is proposed for the power prediction of multiple wind turbines. Starting from the time s...
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Open Access (DOAJ)
DOI: 10.3389/fenrg.2021.723775
Mingyu Zhao, Shujia Zhang, Ke Li, Yanru Zhang et al. • Frontiers in Robotics and AI
(2026)
Densely populated enclosed environments, characterized by complex thermal stratification and overlapping breathing zones, represent high-risk clusters for the airborne transmission of respiratory pathogens. To address the dual challenges of...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/frobt.2026.1846010