Titlebook: Dynamics of Information Systems; 6th International Co Hossein Moosaei,Milan Hladík,Panos M. Pardalos Conference proceedings 2024 The Editor

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,A Collaborative Multi-objective Approach for Clustering Task Based on Distance Measures and Clustere decision-maker to support their final choice, considering all solutions provided by the measured combination. The methodology was tested in a benchmark dataset and also in a real dataset, and in both cases, the results were satisfactory to define the optimal number of clusters and to classify the

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Iranian Architectural Styles Recognition Using Image Processing and Deep Learning,This system can be integrated into military equipment to help identify the architectural style of a building and determine its construction date. By doing so, it can provide a critical warning to prevent the targeting of historically significant structures. To support our system, we have curated a d

WATER

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,Improving Handwritten Cyrillic OCR by Font-Based Synthetic Text Generator,g the synthetic data with the TrOCR-Base-384 model on both datasets. More precisely, we reduced the relative error in terms of CER/WER on (i) HKR-Test1 with OoV samples by around ./., and (ii) NKVD dataset by . CER and . WER. The FbSTG code is available at: ..

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Strategic Decision-Making in Trauma Systems,ork enable the creation of the set of all feasible and Pareto-efficient portfolios where limited funding is allocated across numerous resource requests from trauma centers, hospitals and EMS providers. Using the computational framework, decision-makers can quantitatively analyze the impact of each f

Valves

,An Evolutionary Approach to Automated Class-Specific Data Augmentation for Image Classification, of CNNs required to evaluate each combination. Here, we present an evolutionary approach using a genetic algorithm (GA) to search for an optimal combination of class-specific transformations subject to a feasible time constraint. Our study demonstrates a GA finding augmentation strategies that are

Geyser

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Masculinities in Early Hellenistic Athensss, surprise, fear, anger, and disgust. According to our research, these facial expressions were classified into 12 classes of facial motion vectors. We applied our proposed analysis mechanism to the extended Cohen-Kanade facial expression dataset. Our developed automatic facial expression system ac

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Masculinities in Early Hellenistic Athenstify the riskiness of some unsampled locations in order to select the new areas to be monitored. Moreover, two different decision criteria have been introduced, both depending on the risk level of the occurrence of extreme phenomena under investigation and involving the analysis of monitoring and no

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