الصفحة 1
الصفحة 1
Image Analysis and Recognition ; 17th International Conference, ICIAR 2020, Póvoa de Varzim, Portugal, June 24–26, 2020, Proceedings, Part II
This two-volume set LNCS 12131 and LNCS 12132 constitutes the refereed proceedings of the 17th International Conference on Image Analysis and Recognition, ICIAR 2020, held in Póvoa de Varzim, Portugal, in June 2020. The 54 full papers presented together with 15 short papers were carefully reviewed and selected from 123 submissions. The papers are organized in the following topical sections: image processing and analysis; video analysis; computer vision; 3D computer vision; machine learning; medical image and analysis; analysis of histopathology images; diagnosis and screening of ophthalmic diseases; and grand challenge on automatic lung cancer patient management.
Evolutionary Intelligence : An introduction to theory and applications with Matlab
This book gives a good introduction to evolutionary computation for those who are first entering the field and are looking for insight into the underlying mechanisms behind them. Emphasizing the scientific and machine learning applications of genetic algorithms instead of applications to optimization and engineering, the book could serve well in an actual course on adaptive algorithms.
Data mining and machine learning applications
Elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data.
Machine Learning Applications in Civil Engineering
Discusses machine learning and deep learning models for different civil engineering applications. These models work for stochastic methods wherein internal processing is done using randomized prototypes. The book explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency. It introduces Machine Learning and its applications to different Civil Engineering tasks, including Basic Machine Learning Models for data pre-processing, models for data representation, classification models for Civil Engineering Applications, Bioinspired Computing models for Civil Engineering, and their case studies.
