Titlebook: Recent Challenges in Intelligent Information and Database Systems; 14th Asian Conferenc Edward Szczerbicki,Krystian Wojtkiewicz,Marek Krót

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,Improving Autoencoders Performance for Hyperspectral Unmixing Using Clustering,nable effective analysis of such data, spectral unmixing is often used. It is an important task in hyperspectral imaging, allowing one to obtain the information about spectral endmembers which make up each hyperspectral pixel. This task, traditionally solved with dedicated statistical methods, has r

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艺术

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,Supervised Learning Use to Acquire Knowledge from 2D Analytic Geometry Problems,the theme of identifying geometric elements in unstructured documents and their classification. The proposed solution is based on the automatic recognition of geometric elements, achieved with the help of supervised learning. The chosen system is based on a model resulting from an automatic learning

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,Using Brain-Computer Interface (BCI) and Artificial Intelligence for EEG Signal Analysis,stion whether it is possible to create a classifier that could correctly recognize emotions from EEG data recorded by simple and cheap equipment. In the paper, we compared the created classifier with the one that was taught on high-quality EEG data, which was recorded with the help of professional-g

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Predicting Metastasis-Free Survival Using Clinical Data in Non-small Cell Lung Cancer,ity of lung cancer is the development of local and distant metastases. Lung cancer patients mostly die because of distant metastases rather than the primary tumor. Thus, here we tackle the problem of predicting when a patient relapse with a distant metastatic tumor. This information is relevant not