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Academic Articles & Research Papers
Showing 20 of 23 academic articles
Xiaoqing Gu, Cong Zhang, Tongguang Ni • IEEE Access
(2019)
The rule-based fuzzy systems have successfully applied for numerous medical data classification problems. However, structuring the concise and interpretable fuzzy rules with good classification performance is still a big challenge. To addre...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2954707
Shuzhi Su, Penglian Gao, Yanmin Zhu, Xingzhu Liang et al. • IEEE Access
(2021)
In multi-view learning, massive literature is devoted to exploring the intrinsic structure between cross-views. It is well known that canonical correlation analysis (CCA) is a conventional multi-view learning method, which considers the cor...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3118023
Federica Cuna, Maria Bossa, Fabio Gargano, Mario Nicola Mazziotta • Particles
(2025)
The application of advanced Artificial Intelligence (AI) techniques in astroparticle experiments represents a major advancement in both data analysis and experimental design. As space missions become increasingly complex, integrating AI too...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/particles8040099
Pratikkumar Chauhan, Munindra Lunagaria, Deepak Kumar Verma, Krunal Vaghela et al. • IEEE Access
(2024)
Classification of brain tumour is critical in medical image analysis and diagnosis as it aids in determining the affinity of cases to select treatment paths. This feature underscores the importance of accurate classification of brain tumour...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3460380
Jingmin An, Xiaogang Weng • BMC Bioinformatics
(2022)
Abstract Pre-trained natural language processing models on a large natural language corpus can naturally transfer learned knowledge to protein domains by fine-tuning specific in-domain tasks. However, few studies focused on enriching such p...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12859-022-05031-z
Yumin Zhang, Yanyong Wang • EURASIP Journal on Image and Video Processing
(2025)
Abstract Due to the rapid advances in computer vision and deep learning, human action recognition has become one of the most important representative tasks for video understanding. Especially for human action recognition based on RGB-D data...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13640-025-00677-0
Lijie Geng, Pengji Yan, Zhikun Ji, Chunyu Song et al. • Journal of Cotton Research
(2024)
Abstract Background The lint percentage of seed cotton is one of the most important parameters for evaluating seed cotton quality and affects its price. The traditional measuring method of lint percentage is labor-intensive and time-consumi...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s42397-024-00178-x
Dan Wu, Yanzhi Wang, Yuqi Fei, Guowang Gao • IEEE Access
(2025)
Model size and inference speed have brought about major challenges for the deployment of Convolutional Neural Networks (CNNs) in many applications. An effective approach to address this issue is model quantization, which achieves network co...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3551802
Om Khare, Sunil Mane, Harshmohan Kulkarni, Ninad Barve • Discover Artificial Intelligence
(2024)
Abstract Plant diseases significantly threaten global agriculture, impacting crop yield and food security. Nearly 30% of the crop yield is lost due to plant diseases. Efficient identification and classification of plant diseases through com...
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Open Access (DOAJ)
DOI: 10.1007/s44163-024-00150-3
Vladyslav Yavtukhovskyi, Violeta Tretynyk • Кібернетика та комп'ютерні технології
(2025)
Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. They have achieved great success both in research and in practical applications in recent years, however, on...
DOAJ
Open Access (DOAJ)
DOI: 10.34229/2707-451X.25.2.6
James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness et al. • Proceedings of the National Academy of Sciences
(2017)
The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitabl...
OPENALEX
Open Access
DOI: https://doi.org/10.1073/pnas.1611835114
PMC: 5380101
Yao He, Jing Yang, Shaobo Li, Jianjun Hu et al. • Complex & Intelligent Systems
(2024)
Abstract Catastrophic forgetting in neural networks is a common problem, in which neural networks lose information from previous tasks after training on new tasks. Although adopting a regularization method that preferentially retains the pa...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s40747-024-01350-1
Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad-Khasmakhi et al. • ACM Computing Surveys
(2021)
Deep learning--based models have surpassed classical machine learning--based approaches in various text classification tasks, including sentiment analysis, news categorization, question answering, and natural language inference. In this art...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3439726
Zetian Zhou, Heqing Zhang, Mehdi Effatparvar • Scientific Reports
(2024)
Abstract Sports image classification is a complex undertaking that necessitates the utilization of precise and robust techniques to differentiate between various sports activities. This study introduces a novel approach that combines the de...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-024-64826-7
Alexander Craik, Yongtian He, Jose Luis Contreras-Vidal • Journal of Neural Engineering
(2019)
OBJECTIVE: Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain-computer interfaces, BCI's), and even commercial applications. Many of the analyti...
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DOI: https://doi.org/10.1088/1741-2552/ab0ab5
Jaya Gupta, Sunil Kumar Pathak, Gireesh Kumar • Journal of Physics Conference Series
(2022)
Abstract Deep Learning is a machine learning area that has recently been used in a variety of industries. Unsupervised, semi-supervised, and supervised-learning are only a few of the strategies that have been developed to accommodate differ...
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DOI: https://doi.org/10.1088/1742-6596/2273/1/012029
Shahbaz Rezaei, Xin Liu • IEEE Communications Magazine
(2019)
Traffic classification has been studied for two decades and applied to a wide range of applications from QoS provisioning and billing in ISPs to security-related applications in firewalls and intrusion detection systems. Port-based, data pa...
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Open Access
DOI: https://doi.org/10.1109/mcom.2019.1800819
Jörn Lötsch, Alfred Ultsch • Pain
(2017)
1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...
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DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
Dana Pessach, Erez Shmueli • ACM Computing Surveys
(2022)
An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging from healthcare, transportation, and education to college ad...
OPENALEX
DOI: https://doi.org/10.1145/3494672
Binbin Chen, Shengjie Long • IEEE Access
(2020)
In traditional financial analysis discriminant analyses with statistic methods are considered as primary and widely applied corporate credit rating bases in which human impact plays an essential role. Machine learning approaches enormously ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3036469