Search Results - S.I.: Timely Advances of Deep Learning with applications and Data Driven Modeling

Advances in Deep Learning-Driven Metasurface Design and Application in Holographic Imaging by Lv, Manxu, Feng, Huizhen, Jin, Yongxing, Tian, Ying

“…; however, reviews on this topic remain scarce. This review introduces the development of neural networks and the relevant content on metasurface design using the four types of networks and the applications of deep learning-designed metasurface holographic imaging technology, thereby enhancing readers’ systematic understanding of such technologies…”
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Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches: Theory and Practical Applications by Harrou, Fouzi, Sun, Ying, Hering, Amanda S, Madakyaru, Muddu, Dairi, abdelkader

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Advances in deep learning-driven photo identification and meta analysis of cetaceans in large data repositories by Barnhill, Alexander, Towers, Jared R., Shaw, Tasli J.H., Arias, Magdalena, Bécares, Adrián, Doniol-Valcroze, Thomas, von Fersen, Lorenzo, Genoves, Rodrigo, Rörup, Tim, Sutton, Gary J., Thornton, Sheila, Weiss, Michael, Maier, Andreas, Nöth, Elmar, Bergler, Christian

“… We present a scalable, end-to-end framework that automates this process using lightweight deep learning models optimized for resource-constrained environments…”
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Leveraging advances in data-driven deep learning methods for hybrid epidemic modeling by Chen, Shi, Janies, Daniel, Paul, Rajib, Thill, Jean-Claude

“…) for more than 12 rounds since early 2021 for informed decision support. We emphasize the importance of deep learning techniques for epidemic modeling via a flexible DD…”
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From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare by Chakraborty, Chiranjib, Bhattacharya, Manojit, Pal, Soumen, Lee, Sang-Soo

“… The medicine and healthcare sector has been evolving and advancing very fast. The advancement has been initiated and shaped by the applications of data-driven, robust, and efficient machine learning (ML) to deep learning (DL) technologies…”
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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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Data-Driven Optimization under Uncertainty in the Era of Big Data and Deep Learning: General Frameworks, Algorithms, and Applications by Ning, Chao

“…This dissertation deals with the development of fundamental data-driven optimization under uncertainty, including its modeling frameworks, solution algorithms, and a wide variety of 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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The application of deep learning in data-driven modeling of process industries by Xiaofeng YUAN, Yalin WANG, Chunhua YANG, Weihua GUI

“… industries.Firstly,the history of deep learning was introduced.Then,four widely used deep networks and their applications were introduced in data-driven modeling of process…”
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Application of Machine Learning Method of Data-Driven Deep Learning Model to Predict Well Production Rate in the Shale Gas Reservoirs by Han, Dongkwon, Kwon, Sunil

“… Since we need to simulate the physical phenomenon of multi-stage hydraulic fracturing. To overcome these limitations, this paper presents an alternative proxy model based on data-driven deep learning model…”
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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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Advances in Prior-Driven Machine Learning Techniques for Health Applications With Limited Data by Saffarpour, Mahya

“…Adoption of machine learning (ML) techniques in healthcare applications is hindered by several challenges, including difficulty in accessing large volumes of retrospective data due to regulatory constraints, or the cost and delay…”
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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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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

“…Low-resource languages in natural language processing present unique challenges, marked by limited linguistic resources and sparse data…”
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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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Conditioned fully convolutional denoising autoencoder for multi-target NILM by García, Diego, Pérez, Daniel, Papapetrou, Panagiotis, Díaz, Ignacio, Cuadrado, Abel A., Enguita, José M., Domínguez, Manuel

“… Advances in data-driven models provide techniques like Non-Intrusive Load Monitoring (NILM), which estimates the energy demand of appliances from total consumption…”
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Memetic algorithm-based optimization of hybrid forecasting systems for multivariate time series by Padilha, Guilherme Afonso Galindo, Jung, Jason J., de Mattos Neto, Paulo S. G.

“…), a hybrid system that combines linear statistical and deep learning (DL) models employing a novel memetic algorithm (MA…”
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