Artificial Intelligence and Big Data Applications

Contributors: Ramdane-Cherif, Amar, Tomar, Ravi, Singh, Thipendra

Subject Terms: artificial intelligence, deep learning, attention module, feature fusion, magnetic resonance imaging, traffic flow forecasting, graph neural networks, Artificial Intelligence, high-value data, open-government data, federated learning, model aggregation, knowledge distillation, uncertainty in deep neural networks, association rules, defect analysis, automobile repair, decision support, web service, information retrieval, biomedical terminologies, multinomial naive Bayesian classifier, Bayesian networks, brain extraction, brain multi-structure segmentation, cloud computing, double-stage 3D U-Net, neuroradiology, 7T magnetic resonance, volume measure analysis, hybrid DCNN mechanism, diagnosis, chest X-ray images, radiography images, lung opacity, pneumonia, COVID-19, blockchain, tokenized markets, tokenized platforms, digital assets, cybersecurity, virtual economy, European dataspace, extended reality, big data, human-computer interaction, persuasive technologies, mobile health monitoring apps, persuasive system design model, e-commerce sales, e-commerce turnover, e-commerce web sales, digital economy, sustainable development, COVID-19 analytics, analysing COVID-19 discourse, social media analytics, regression, topic analysis, Kolmogorov–Gabor polynomials, length of stay, hospital capacity, regularized least squares, validation studies, data generation, anomaly data, user behavior generation, data analytics, Technology: general issues

File Description: application/octet-stream

Access URL: https://directory.doabooks.org/handle/20.500.12854/137717
https://mdpi.com/books/pdfview/book/8946

Uncertainty quantification in multi-class image classification using chest X-ray images of COVID-19 and pneumonia

Authors: Albert Whata, Katlego Dibeco, Kudakwashe Madzima, Ibidun Obagbuwa

Source: Frontiers in Artificial Intelligence, Vol 7 (2024)

Subject Terms: uncertainty quantification deep neural networks, Bayesian neural networks, Monte Carlo dropout, Ensemble Monte Carlo, chest-X-ray, classification metrics, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/frai.2024.1410841/full; https://doaj.org/toc/2624-8212

Access URL: https://doaj.org/article/c282d649d37a4e37a39e54b04e4284bd

FedUA: An Uncertainty-Aware Distillation-Based Federated Learning Scheme for Image Classification

Authors: Shao-Ming Lee, Ja-Ling Wu

Source: Information, Vol 14, Iss 4, p 234 (2023)

Subject Terms: federated learning, model aggregation, knowledge distillation, uncertainty in deep neural networks, Information technology, T58.5-58.64

File Description: electronic resource

Relation: https://www.mdpi.com/2078-2489/14/4/234; https://doaj.org/toc/2078-2489

Access URL: https://doaj.org/article/fcaae3e44c9844bbb4cadab3b8f95b77