Artificial neural networks evolutionary (7 Ergebnisse)

Zustand: New. In English.

Zustand: New.

Taschenbuch. Zustand: Neu. Modeling of Artificial Neural Networks using Evolutionary Algorithms | Evolutionary Computations | G. V. R. Sagar | Taschenbuch | 200 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659896439 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Paperback. Zustand: Brand New. 200 pages. 8.66x5.91x0.46 inches. In Stock.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.…

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.…

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 1034 | Sprache: Englisch | Produktart: Bücher | Proceedings of the Artificial Neural Networks in Engineering Conference, November 12-15, 1995 St. Louis, Missouri. Heightened interest in engineering applications of neutral networks in recent years has led to intense research in the field. Volume 5 of this highly successful series boasts the contribution of researchers from 20 countries. They examine the theory and applications of artificial neural networks, fuzzy logic, and evolutionary programming. The volume provides referred versions of the latest developments in design and manufacturing engineering, including comprehensive coverage of: Artificial neural network architecture; Fuzzy networks and systems; Evolutionary programming; Pattern recognition; Adaptive control; Smart engineering system design.…