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Image Analysis
The two-volume set LNCS 10269 and 10270 constitutes the refereed proceedings of the 20th Scandinavian Conference on Image Analysis, SCIA 2017, held in Tromsø, Norway, in June 2017. The 87 revised papers presented were carefully reviewed and selected from 133 submissions. The contributions are structured in topical sections on history of SCIA; motion analysis and 3D vision; pattern detection and recognition; machine learning; image processing and applications; feature extraction and segmentation; remote sensing; medical and biomedical image analysis; faces, gestures and multispectral analysis.
Computational Intelligence
The present book includes a set of selected extended papers from the sixth International Joint Conference on Computational Intelligence (IJCCI 2014), held in Rome, Italy, from 22 to 24 October 2014. The conference was composed by three co-located conferences: The International Conference on Evolutionary Computation Theory and Applications (ECTA), the International Conference on Fuzzy Computation Theory and Applications (FCTA), and the International Conference on Neural Computation Theory and Applications (NCTA). Recent progresses in scientific developments and applications in these three areas are reported in this book. IJCCI received 210 submissions, from 51 countries, in all continents. Af...
Artificial Intelligence Applications and Reconfigurable Architectures
ARTIFICIAL INTELLIGENCE APPLICATIONS and RECONFIGURABLE ARCHITECTURES The primary goal of this book is to present the design, implementation, and performance issues of AI applications and the suitability of the FPGA platform. This book covers the features of modern Field Programmable Gate Arrays (FPGA) devices, design techniques, and successful implementations pertaining to AI applications. It describes various hardware options available for AI applications, key advantages of FPGAs, and contemporary FPGA ICs with software support. The focus is on exploiting parallelism offered by FPGA to meet heavy computation requirements of AI as complete hardware implementation or customized hardware acce...
Machine Learning for Time Series Forecasting with Python
Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling. Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment ...
Short-Term Load Forecasting using Machine Learning Methods
Maintaining the balance between generation and consumption is at the heart of electricity grid operation. A disruption to this balance can lead to grid overloads, outages, system damage, rising electricity costs or wasted electricity. For this reason, accurate forecasting of load behavior is crucial. In this work, two classes of ML-based algorithms were used for load forecasting: the Hidden Markov Models (HMMs) and the Deep Neural Networks (DNNs), both of which provide stable and more accurate results than the considered benchmark methods. HMMs could be successfully used as a stand-alone predictor with a training based on Maximum Likelihood Estimation (MLE) in combination with a clustering o...
Proceedings of NetSci-X 2020: Sixth International Winter School and Conference on Network Science
This volume constitutes the proceedings of NetSci-X 2020: the Sixth International School and Conference on Network Science, which was held in Tokyo, Japan, in January 2020. NetSci-X is the Network Science Society’s winter conference series that covers a wide variety of interdisciplinary topics on networks. Participants come from various fields, including (but not limited to): mathematics, physics, computer science, social sciences, management and marketing sciences, organization science, communication science, systems science, biology, ecology, neuroscience, medicine, as well as business. This volume consists of contributed papers that have been accepted to NetSc-X 2020 through a rigorous peer review process. Researchers, students, and professionals will gain first-hand information about today’s cutting-edge research frontier of network science.
