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Data Complexity in Pattern Recognition
Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.
R 4,656.62
Proceedings of the 15th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2023)
This book presents 57 selected papers focused on Smart Health Care from the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2023) and 14th World Congress on Nature and Biologically Inspired Computing (NaBIC 2023), which was held in 5 different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India and in online mode. SoCPaR – NaBIC 2023 had contributions by authors from 39 countries. This Volume offers a valuable reference guide for all medical doctors, scientists, academicians, researchers, students and practitioners in the field of artificial intelligence and smart health care.
R 8,059.00
Proceedings of the 15th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2023)
This book presents 55 selected papers focused on Deep Learning and Large Language Models from the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2023) and 14th World Congress on Nature and Biologically Inspired Computing (NaBIC 2023). SoCPaR – NaBIC 2023 was held in 5 different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India and in online mode. The conference had contributions by authors from 39 countries. This Volume offers a valuable reference guide for all scientists, academicians, researchers, students and practitioners focused on advanced machine learning including deep learning methods, large language models and its real-world applications.
R 9,158.00
Data Complexity in Pattern Recognition
Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.
R 5,439.08
