Search Results - Special Issue on Timely Advances of Deep Learning with applications and Data Driven Modeling

Editorial: Introduction to the Special Issue on AI, Machine Learning, and Deep Learning: Advances and Applications for EMC by Duffy, Alistair, Liu, En-Xiao

“…). While AI has been a staple of science fiction for decades with actual applications in engineering and sciences for many years, it is only in the last year or so that generative AI tools have enthused…”
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Call for Papers: Special Issue on AI, Machine Learning, and Deep Learning: Advances and Applications for EMC

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Call for Papers: Special Issue on AI, Machine Learning, and Deep Learning: Advances and Applications for EMC

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Call for Papers: Special Issue on AI, Machine Learning, and Deep Learning: Advances and Applications for EMC

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Advances in physics-informed deep learning for imaging data: a review of methods and applications by Yogita, Yogita, Bocklitz, Thomas

“…Deep learning (DL) has transformed numerous application domains owing its ability to automatically extract features from data…”
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Deep learning-based advances and applications for single-cell RNA-sequencing data analysis by Bao, Siqi, Li, Ke, Yan, Congcong, Zhang, Zicheng, Qu, Jia, Zhou, Meng

“… In the present study, recent advances and applications of deep learning-based methods, together with specific tools for scRNA-seq data analysis, were summarized…”
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IEEE Access Special Section Editorial: Trends and Advances in Bio-Inspired Image-Based Deep Learning Methodologies and Applications by Peer, Peter, Travieso-Gonzalez, Carlos M., Asari, Vijayan K., Dutta, Malay Kishore

“…Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency…”
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Special issue on Recent Advances in Fuzzy Deep Learning for Uncertain Medicine Data by Ding, Weiping, Liu, Jun, Lin, Chin‐Teng, Mrozek, Dariusz

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Special issue: Recent advances in deep learning, biometrics, health informatics and data science by Fernandes, Steven Lawrence, Martis, Roshan Joy, Lin, Hong, Javadi, Bahman, Tanik, Urcun John, Sharif, Muhammad

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Neurocomputing guest editorial for the special issue: Advances in deep and shallow machine learning approaches for handling data irregularities by Das, Swagatam, Garcia, Salvador, Triguero, Isaac

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CJRS' Special Issue on Deep Learning for Environmental Applications of Remote Sensing Data by Mahdianpari, Masoud, Homayouni, Saeid, Foucher, Samuel

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XCSR Learning from Compressed Data Acquired by Deep Neural Network by Matsumoto, Kazuma, Tatsumi, Takato, Sato, Hiroyuki, Kovacs, Tim, Takadama, Keiki

“…The correctness rate of classification of neural networks is improved by deep learning, which is machine learning of neural networks, and its accuracy is higher than the human brain in some fields…”
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Deep learning approaches and data augmentation for melanoma detection by Alzamel, Mai, Iliopoulos, Costas, Lim, Zara

“… Machine learning (ML) and deep learning (DL) techniques have shown a promising results in prediction and classification tasks…”
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Call for Special Issue Papers: Deep Learning Assisted Big Data Analytics for Biomedical Applications and Digital Healthcare by Wang, Gai-Ge, Gao, Xiao-Zhi, Pei, Yan

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Call for Special Issue Papers: Deep Learning Assisted Big Data Analytics for Biomedical Applications and Digital Healthcare by Wang, Gai-Ge, Gao, Xiao-Zhi, Pei, Yan

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Editor’s Note - Special Issue on Deep vs. Shallow: Learning for Emerging Web-scale Data Computing and Applications

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Exploring distribution-based approaches for out-of-distribution detection in deep learning models by Carvalho, Thiago, Vellasco, Marley, Amaral, José Franco

“…Detecting unknown samples is a crucial task for deep learning applications, especially when considering open-set problems such as autonomous driving or disease classification…”
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CM-MLP: hybrid convmixer-deep MLP architecture for enhanced identification of corn and apple leaf diseases by Li, Li-Hua, Tanone, Radius

“… We propose a novel hybrid ConvMixer and Deep MLP architecture called CM-MLP that combines the strengths of ConvMixer with various Deep Multi-layer Perceptron (MLP…”
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Researching the detection of continuous gravitational waves based on signal processing and ensemble learning by Pintelas, Emmanuel, Livieris, Ioannis E., Pintelas, Panagiotis

“…). In contrast to the complex burst nature of B-GWs, C-GWs have an elegant and significantly simpler form while they are able to provide higher quality data for the exploration of the universe…”
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Assessment and deployment of a LSTM-based virtual sensor in an industrial process control loop by González-Herbón, Raúl, González-Mateos, Guzmán, Rodríguez-Ossorio, José R., Prada, Miguel A., Morán, Antonio, Alonso, Serafín, Fuertes, Juan J., Domínguez, Manuel

“… Data-driven techniques are well-suited for this aim, given their capacity to model potentially complex industrial processes…”
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