Titlebook: Data Intelligence and Cognitive Informatics; Proceedings of ICDIC I. Jeena Jacob,Selvanayaki Kolandapalayam Shanmuga Conference proceedings

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2524-7565 ork in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.978-981-19-6006-2978-981-19-6004-8Series ISSN 2524-7565 Series E-ISSN 2524-7573

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https://doi.org/10.1007/978-3-8348-8675-0ul and non-stressful situations is known as voice analysis, as well as investigating how the voice changes in stressful situations in humans. The goal of this research is to use speech signals to predict stress. In MATLAB, several spectral properties from voice are retrieved. The gathered results ar

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Software Evolution and Modernisations empirical studies, DenseNet121 architecture proved out to be best giving the accuracy of about 89.2% on binary classification, and ResNet50 architecture gave the best results when it came to the multi-class classification with the accuracy of about 93.87%. Both of these models are deployed onto th

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Robin Ciardullo,Richard Harms,Holland Ford access this portal, as it is easy to operate. The data shown by the portal are up to date and updated real time. Service providers who are in the similar field will get benefited from it, as this Web site performs as an interface between users and service providers. The accomplishments of this work

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https://doi.org/10.1007/978-3-319-97788-1of detectors. It was discovered that while testing with the existing method, the rate of error increases; however, when the recommended adaptive approach was used, the spoof detection and performance gets improved significantly.

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Robert Mies,Jérémy Bonvoisin,Roland Jochemipment this paper also supports future scalability to represent it in an analytical format. In the first approach, the model implements the CNN model and, in the second approach, implements the VGG16 model, eventually comparing the accuracy of the result for further using the best model to deploy on