Titlebook: Computational Collective Intelligence; 16th International C Ngoc Thanh Nguyen,Bogdan Franczyk,Adrianna Kozierk Conference proceedings 2024

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Alexander Verweyen,Gregor Eckert Computed Tomography (CT) images collected from COVID-19 patients and healthy lungs reveal the promising combination between the image classification of VGG-16 and interpretation methods of Grad-CAM and LIME in lung disease diagnosis.

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Susanne Ring-Dimitriou,Martin Pühringercorporating with various prompt templates. It is implemented by integrating into Trivi, a customer-intelligent platform for SMEs. An experiment was carried out to evaluate its performance, using different datasets, revealing that this approach is slightly better than previous works.

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Collective Computational Intelligence Challenges and Opportunitiespected to appear sometime in the future. Next, we discuss technologies shaping current-generation CCI systems including generative AI, intelligent agents, and ANN technologies. Based on the above we evaluate developments leading towards Artificial General Intelligence and General Collective Computational Intelligence.

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Interpreting Results of VGG-16 for COVID-19 Diagnosis on CT Images Computed Tomography (CT) images collected from COVID-19 patients and healthy lungs reveal the promising combination between the image classification of VGG-16 and interpretation methods of Grad-CAM and LIME in lung disease diagnosis.

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BABot: A Framework for the LLM-Based Chatbot Supporting Business Analytics in e-Commercecorporating with various prompt templates. It is implemented by integrating into Trivi, a customer-intelligent platform for SMEs. An experiment was carried out to evaluate its performance, using different datasets, revealing that this approach is slightly better than previous works.

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Reward-Based Hybrid Genetic Algorithm for Solving the Class Scheduling Problemin the proposed algorithm. While the fulfilment of hard conditions is mandatory, the satisfaction of soft constraints is evaluated through rewards, which are assigned based on the degree to which the constraints are met. The genetic algorithm proposed in this article validates potential solutions by

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