Artificial Neural Networks and Evolutionary Computation in Remote Sensing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Neural Networks and Evolutionary Computation in Remote Sensing write by Taskin Kavzoglu. This book was released on 2021-01-19. Artificial Neural Networks and Evolutionary Computation in Remote Sensing available in PDF, EPUB and Kindle. 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.
Application of Artificial Neural Networks in Geoinformatics
Application of Artificial Neural Networks in Geoinformatics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Application of Artificial Neural Networks in Geoinformatics write by Saro Lee. This book was released on 2018-04-09. Application of Artificial Neural Networks in Geoinformatics available in PDF, EPUB and Kindle. This book is a printed edition of the Special Issue "Application of Artificial Neural Networks in Geoinformatics" that was published in Applied Sciences
Pathological Brain Detection
Pathological Brain Detection - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Pathological Brain Detection write by Shui-Hua Wang. This book was released on 2018-07-20. Pathological Brain Detection available in PDF, EPUB and Kindle. This book provides detailed practical guidelines on how to develop an efficient pathological brain detection system, reflecting the latest advances in the computer-aided diagnosis of structural magnetic resonance brain images. Matlab codes are provided for most of the functions described. In addition, the book equips readers to easily develop the pathological brain detection system further on their own and apply the technologies to other research fields, such as Alzheimer’s detection, multiple sclerosis detection, etc.
Applications of Artificial Neural Networks for Nonlinear Data
Applications of Artificial Neural Networks for Nonlinear Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applications of Artificial Neural Networks for Nonlinear Data write by Patel, Hiral Ashil. This book was released on 2020-09-25. Applications of Artificial Neural Networks for Nonlinear Data available in PDF, EPUB and Kindle. Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.
Artificial Neural Networks for Engineering Applications
Artificial Neural Networks for Engineering Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Neural Networks for Engineering Applications write by Alma Y. Alanis. This book was released on 2019-03-15. Artificial Neural Networks for Engineering Applications available in PDF, EPUB and Kindle. Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications. Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering Contains all the theory required to use the proposed methodologies for different applications
