The article discusses the main tasks of machinelearning. The functional structure of a computer algorithm for solving machinelearning problems and a datamining model are considered. The solution of the simplest mac...
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With the rapid development of artificial intelligence technology, the automatic recognition of students' learning state and emotion by target detection and expression recognition technology has attracted more and ...
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The conventional cloud computing paradigm has spurred the development of innovative architectures for next-generation cloud computing. These novel designs can effectively manage vast amounts of data, which was previou...
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This paper uses the machine vision method to identify the skirt module. We have constructed three kinds of machinerecognition models of skirt profile processing, structure analysis of style drawing, and size estimati...
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The cryptographic techniques that underpin current network security standards run the risk of becoming outdated due to the advancement of quantum computing. Researchers and industry professionals are working to create...
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Predicting learning outcomes (LO) is an important problem in educational datamining (EDM). Despite extensive research, there remains a gap in determining the optimal timing for predicting early LO with acceptable acc...
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In contemporary society, conventional notice boards encounter challenges in terms of accessibility and engagement, especially within educational institutions where effective information dissemination is vital. By impl...
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Cyber security requires detecting and stopping wireless sensor network attacks. We introduce a fast super deep learning model for cloud-based WSN attack detection in this research. Our offline approach divides data in...
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To assess student engagement in an e-learning environment, this work proposes a novel learning analytics dataset collection that combines emotional, cognitive, and behavioral data. The dataset includes facial expressi...
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ISBN:
(纸本)9783031451690;9783031451706
To assess student engagement in an e-learning environment, this work proposes a novel learning analytics dataset collection that combines emotional, cognitive, and behavioral data. The dataset includes facial expressions recorded by a webcam during e-learning sessions and log data such as play, pause, seek, course views, course material views, lecture views, quiz responses, etc. The procedure for gathering the data and the difficulties encountered are covered in the study. Combining emotional, cognitive, and behavioral cues for engagement detection in e-learning settings is made possible by this dataset, which represents a significant advancement in the field of learning analytics.
Fingerprints are used in many fields as important biological data of people. As one of people's important personal privacy, fingerprints are also prone to leakage. Images and videos posted on social media are invi...
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