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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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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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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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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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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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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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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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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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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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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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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

“…The detection of Gravitational Waves has introduced a new era for physics, astronomy, and astrophysics, unveiling new universe mysteries. Unfortunately,…”
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Zero-day Android botnet detection using neural networks by Seraj, Saeed, Pimenidis, Elias, Trovati, Marcello, Polatidis, Nikolaos

“…Android devices have evolved to offer a diverse array of services, spanning applications related to banking, business, health, and entertainment…”
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DACL+: domain-adapted contrastive learning for enhanced low-resource language representations in document clustering tasks by Zaikis, Dimitrios, Vlahavas, Ioannis

“… To this end, we introduce a domain-adapted contrastive learning approach for low-resource Greek document clustering…”
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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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Feature analysis and ensemble-based fault detection techniques for nonlinear systems by Bolboacă, Roland, Haller, Piroska, Genge, Bela

“…Machine learning approaches play a crucial role in nonlinear system modeling across diverse domains, finding applications in system monitoring, anomaly/fault detection, control, and various other areas…”
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A fuzzy zeroing neural network and its application on dynamic Hill cipher by Jin, Jie, Lei, Xiaoyang, Chen, Chaoyang, Lu, Ming, Wu, Lianghong, Li, Zhijing

“…Cryptography is the core of information security, and the Hill cipher is one of the most important methods for cryptography. For the purpose of the improvement…”
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