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E-grāmata: 19th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO 2024: Salamanca, Spain, October 9-11, 2024 Proceedings, Volume 2

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This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at the SOCO 2024 conference held in the beautiful and historic city of Salamanca (Spain) in October 2024.





Soft computing represents a collection or set of computational techniques in machine learning, computer science, and some engineering disciplines that investigate, simulate, and analyze very complex issues and phenomena.





After a thorough peer-review process, the 18th SOCO 2023 International Program Committee selected 62 papers for publication in these conference proceedings, representing an acceptance rate of 50%. In this relevant edition, a particular emphasis was put on organizing special sessions. Four special sessions were organized related to relevant topics such as Machine Learning and Computer Vision in Industry 4.0, Intelligent Models and Frameworks for Smart Agriculture and Green Economy, Computational Intelligence Applied to Modelling and Control of Engineering Systems, and Applied Machine Learning (2nd Edition).





The selection of papers was extremely rigorous to maintain the high quality of the conference. We want to thank the members of the Program Committees for their hard work during the reviewing process. This is a crucial process for creating a high-standard conference; the SOCO conference would not exist without their help.

.- Part I Special Session: Machine Learning and Computer Vision in Industry 4.0.

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Chapter 1 Computer Vision Based Quality Control for Molding Injection Machines.

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Chapter 2 Towards a comprehensive taxonomy of cobots: A tool for multi-criteria classification.

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Chapter 3 Novel positional encoding methods for neural rendering.

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Chapter 4 Enhancing Object Segmentation via Few-Shot Learning with Limited Annotated Data.

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Chapter 5 Early breast cancer detection by automated analysis of mammograms with deep convolutional networks.

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Chapter 6 Feature Selection for Multi-Label Classification in Predictive Maintenance.

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Chapter 7 Transforming Manufacturing through Human Digital Twins: A New Architectural Approach, etc.

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