Titlebook: Artificial Intelligence and Soft Computing; 22nd International C Leszek Rutkowski,Rafał Scherer,Jacek M. Zurada Conference proceedings 2023

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Conference proceedings 2023nce and Soft Computing, ICAISC 2023, held in Zakopane, Poland, during June 18–22, 2023. ..The 84 revised full papers presented in these proceedings were carefully reviewed and selected from 175 submissions. ..The papers are organized in the following topical sections: ..Part I:  Neural Networks and

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Michel E. Domsch,Sven H. A. Siemersion sequences: grasp, move, position, release, and reach. We present experimental results of gesture recognition achieved by a spatio-temporal graph convolutional neural network on real RGB image sequences.

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Fachlaufbahnen in der Altenpflegeoftware synthesizers to train a universal model. It is a good base for further transfer learning to quickly adapt transcription model for other instruments. Achieved results prove that using synthesized data for training may be a good base for pretraining general-purpose models, where the task of transcription is not focused on one instrument.

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Transfer of Knowledge Among Instruments in Automatic Music Transcriptionoftware synthesizers to train a universal model. It is a good base for further transfer learning to quickly adapt transcription model for other instruments. Achieved results prove that using synthesized data for training may be a good base for pretraining general-purpose models, where the task of transcription is not focused on one instrument.

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An Interpretable Two-Layered Neural Network Structure–Based on Component-Wise Reasoningdden layer, and show that Matching the right objective function with activation function of the output layer, is the key to interpreting the weights and their influence on component-wise classification.

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0302-9743 er Vision, Image and Speech Analysis; Various Problems of Artificial Intelligence; Bioinformatics, Biometrics and Medical Applications; and Data Mining and Pateern Classification... .978-3-031-42504-2978-3-031-42505-9Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Fachkundenachweis Rettungsdienstements for computing complexity. The research showed no significant differences in the Monte Carlo approaches and the corresponding neural network methods. In the case of recursive method invocation, the effectiveness increased compared to the base methods.

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Nicola K. Schorn,Karin Buchholzstics to train an Artificial Neural Network model to estimate the viscosity values of the solutions. The proposed model was able to predict the viscosity value of the samples using the characteristics of their droplets with an accuracy of 83.08% on the test dataset.