Titlebook: Extended Selected Papers of the 14th International Conference on Information, Intelligence, Systems,; IISA2023 Nikolaos Bourbakis,George A.

周兴旺

Reinforcement Learning Agents in Precision Agriculture, has marked an era of enhanced efficiency, productivity, and sustainability through exploiting scientific fields such as Machine Learning, Big Data, Computer Vision, Internet of Things and Robotics being applied in agriculture more and more. Given the frequent need for ongoing decision-making insid

cuticle

Inductive Machine Learning for Classifying Breast Lesions from Imbalanced MRI-B Dataservations of magnetic mammograms. Specifically, magnetic mammography data MRI-data) collected in collaboration with medical experts, are utilized. The proposed methodology combines different stages of data pre-processing (value grouping of variables, filling-in missing values, etc.) in combination

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Clumsy

Digitization of Forensic Engineering: Overview, Perspectives and New Challengeseed of extracting, representing and storing the underlying information. The scope of application is wide and multidisciplinary, as the digitization process now fully involves all phases of the forensic process. Due to the recent innovations in the field of knowledge representation and data analytics

边缘带来墨水

Exaggerate

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TravelTheLake: Promoting Sustainable Lake Development Using Augmented Reality affecting the socioeconomic relations of local inhabitants, food producers and visitors. The application is based on previous research showing that appropriate fishing methods in the lake could have a positive impact on the quality of fishing population, on the income of fishermen and the broader d

昏暗

Few-Shot 1/, Anomalies Feedback: Damage Vision Mining Opportunity and Embedding Feature Imbalancely detection in industrial applications. Specifically, for condition-based maintenance, automating visual inspection is crucial to ensure high quality. Deterioration prognostic attempts to optimize the fine decision process for predictive maintenance and proactive repair. In civil infrastructure and

祝贺

STENT

Software Defect Detection Using Machine Learning on Data from Open-Source Programst are defective and those that are not, and it also explores the idea of employing only structural code metrics to achieve that. To categorize files as defective or non-defective, two real-life datasets were used: one from the source code of twenty-six releases of Notepad++ and one from the source c