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

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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Editorial: Introduction to the Special Issue on AI, Machine Learning, and Deep Learning: Advances and Applications for EMC von 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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Deep learning-based advances and applications for single-cell RNA-sequencing data analysis von 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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Advances in physics-informed deep learning for imaging data: a review of methods and applications von 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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IEEE Access Special Section Editorial: Trends and Advances in Bio-Inspired Image-Based Deep Learning Methodologies and Applications von 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: Recent advances in deep learning, biometrics, health informatics and data science von Fernandes, Steven Lawrence, Martis, Roshan Joy, Lin, Hong, Javadi, Bahman, Tanik, Urcun John, Sharif, Muhammad

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Special issue on Recent Advances in Fuzzy Deep Learning for Uncertain Medicine Data von Ding, Weiping, Liu, Jun, Lin, Chin‐Teng, Mrozek, Dariusz

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

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

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

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Deep learning approaches and data augmentation for melanoma detection von 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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Guest editorial: Introduction to the Special Section on Load Balancing of Sensory Data for IoT Deep Learning Applications with Edge/Fog Computing (VSI-lbdl) von Sharma, Bhisham, Koundal, Deepika, Singh, Raman

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Exploring distribution-based approaches for out-of-distribution detection in deep learning models von 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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Assessment and deployment of a LSTM-based virtual sensor in an industrial process control loop von 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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Retracted: Multimedia Data Processing Technology and Application Based on Deep Learning von Multimedia, Advances in

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