Author: IEEE Staff
Publisher:
ISBN: 9781665427937
Category :
Languages : en
Pages : 0
Book Description
IGARSS 2022 covers all aspects of remote sensing science and technology using electromagnetic waves with applications in Earth and planetary remote sensing
IGARSS 2022 2022 IEEE International Geoscience and Remote Sensing Symposium
Author: IEEE Staff
Publisher:
ISBN: 9781665427937
Category :
Languages : en
Pages : 0
Book Description
IGARSS 2022 covers all aspects of remote sensing science and technology using electromagnetic waves with applications in Earth and planetary remote sensing
Publisher:
ISBN: 9781665427937
Category :
Languages : en
Pages : 0
Book Description
IGARSS 2022 covers all aspects of remote sensing science and technology using electromagnetic waves with applications in Earth and planetary remote sensing
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
Author: IEEE Staff
Publisher:
ISBN: 9781665447621
Category :
Languages : en
Pages :
Book Description
Annual Igarss symposium
Publisher:
ISBN: 9781665447621
Category :
Languages : en
Pages :
Book Description
Annual Igarss symposium
Proceedings of the 2nd International Conference on Big Data, IoT and Machine Learning
Author: Mohammad Shamsul Arefin
Publisher: Springer Nature
ISBN: 981998937X
Category :
Languages : en
Pages : 1053
Book Description
Publisher: Springer Nature
ISBN: 981998937X
Category :
Languages : en
Pages : 1053
Book Description
Advances in Machine Learning and Image Analysis for GeoAI
Author: Saurabh Prasad
Publisher: Elsevier
ISBN: 044319078X
Category : Science
Languages : en
Pages : 366
Book Description
Advances in Machine Learning and Image Analysis for GeoAI provides state-of-the-art machine learning and signal processing techniques for a comprehensive collection of geospatial sensors and sensing platforms. The book covers supervised, semi-supervised and unsupervised geospatial image analysis, sensor fusion across modalities, image super-resolution, transfer learning across sensors and time-points, and spectral unmixing among other topics. The chapters in these thematic areas cover a variety of algorithmic frameworks such as variants of convolutional neural networks, graph convolutional networks, multi-stream networks, Bayesian networks, generative adversarial networks, transformers and more.Advances in Machine Learning and Image Analysis for GeoAI provides graduate students, researchers and practitioners in the area of signal processing and geospatial image analysis with the latest techniques to implement deep learning strategies in their research. Covers the latest machine learning and signal processing techniques that can effectively leverage geospatial imagery at scale Presents a variety of algorithmic frameworks, including variants of convolutional neural networks, multi-stream networks, Bayesian networks, and more Includes open-source code-base for algorithms described in each chapter
Publisher: Elsevier
ISBN: 044319078X
Category : Science
Languages : en
Pages : 366
Book Description
Advances in Machine Learning and Image Analysis for GeoAI provides state-of-the-art machine learning and signal processing techniques for a comprehensive collection of geospatial sensors and sensing platforms. The book covers supervised, semi-supervised and unsupervised geospatial image analysis, sensor fusion across modalities, image super-resolution, transfer learning across sensors and time-points, and spectral unmixing among other topics. The chapters in these thematic areas cover a variety of algorithmic frameworks such as variants of convolutional neural networks, graph convolutional networks, multi-stream networks, Bayesian networks, generative adversarial networks, transformers and more.Advances in Machine Learning and Image Analysis for GeoAI provides graduate students, researchers and practitioners in the area of signal processing and geospatial image analysis with the latest techniques to implement deep learning strategies in their research. Covers the latest machine learning and signal processing techniques that can effectively leverage geospatial imagery at scale Presents a variety of algorithmic frameworks, including variants of convolutional neural networks, multi-stream networks, Bayesian networks, and more Includes open-source code-base for algorithms described in each chapter
Signal and Image Processing for Remote Sensing
Author: C.H. Chen
Publisher: CRC Press
ISBN: 1040031250
Category : Technology & Engineering
Languages : en
Pages : 433
Book Description
Advances in signal and image processing for remote sensing have been tremendous in recent years. The progress has been particularly significant with the use of deep learning based techniques to solve remote sensing problems. These advancements are the focus of this third edition of Signal and Image Processing for Remote Sensing. It emphasizes the use of machine learning approaches for the extraction of remote sensing information. Other topics include change detection in remote sensing and compressed sensing. With 19 new chapters written by world leaders in the field, this book provides an authoritative examination and offers a unique point of view on signal and image processing. Features Includes all new content and does not replace the previous edition Covers machine learning approaches in both signal and image processing for remote sensing Studies deep learning methods for remote sensing information extraction that is found in other books Explains SAR, microwave, seismic, GPR, and hyperspectral sensors and all sensors considered Discusses improved pattern classification approaches and compressed sensing approaches Provides ample examples of each aspect of both signal and image processing This book is intended for university academics, researchers, postgraduate students, industry, and government professionals who use remote sensing and its applications.
Publisher: CRC Press
ISBN: 1040031250
Category : Technology & Engineering
Languages : en
Pages : 433
Book Description
Advances in signal and image processing for remote sensing have been tremendous in recent years. The progress has been particularly significant with the use of deep learning based techniques to solve remote sensing problems. These advancements are the focus of this third edition of Signal and Image Processing for Remote Sensing. It emphasizes the use of machine learning approaches for the extraction of remote sensing information. Other topics include change detection in remote sensing and compressed sensing. With 19 new chapters written by world leaders in the field, this book provides an authoritative examination and offers a unique point of view on signal and image processing. Features Includes all new content and does not replace the previous edition Covers machine learning approaches in both signal and image processing for remote sensing Studies deep learning methods for remote sensing information extraction that is found in other books Explains SAR, microwave, seismic, GPR, and hyperspectral sensors and all sensors considered Discusses improved pattern classification approaches and compressed sensing approaches Provides ample examples of each aspect of both signal and image processing This book is intended for university academics, researchers, postgraduate students, industry, and government professionals who use remote sensing and its applications.
Artificial Intelligence for Sustainable Development
Author: Anandakumar Haldorai
Publisher: Springer Nature
ISBN: 3031539729
Category :
Languages : en
Pages : 492
Book Description
Publisher: Springer Nature
ISBN: 3031539729
Category :
Languages : en
Pages : 492
Book Description
Digest
Signal and Information Processing, Networking and Computers
Author: Yue Wang
Publisher: Springer Nature
ISBN: 9819721202
Category :
Languages : en
Pages : 539
Book Description
Publisher: Springer Nature
ISBN: 9819721202
Category :
Languages : en
Pages : 539
Book Description
Artificial Intelligence XL
Author: Max Bramer
Publisher: Springer Nature
ISBN: 3031479947
Category : Computers
Languages : en
Pages : 525
Book Description
This book constitutes the refereed proceedings of the 43rd SGAI International Conference on Artificial Intelligence, AI 2023, held in Cambridge, UK, during December 12–14, 2023. The 27 full papers and 20 short papers included in this book are carefully reviewed and selected from 67 submissions. They were organized in topical sections as follows: Technical Papers: Speech and Natural Language Analysis, Image Analysis, Neural Nets, Case Based Reasoning and Short Technical Papers. Application Papers: Machine Learning Applications, Machine Vision Applications, Knowledge Discovery and Data Mining Applications, other AI Applications and Short Application Papers.
Publisher: Springer Nature
ISBN: 3031479947
Category : Computers
Languages : en
Pages : 525
Book Description
This book constitutes the refereed proceedings of the 43rd SGAI International Conference on Artificial Intelligence, AI 2023, held in Cambridge, UK, during December 12–14, 2023. The 27 full papers and 20 short papers included in this book are carefully reviewed and selected from 67 submissions. They were organized in topical sections as follows: Technical Papers: Speech and Natural Language Analysis, Image Analysis, Neural Nets, Case Based Reasoning and Short Technical Papers. Application Papers: Machine Learning Applications, Machine Vision Applications, Knowledge Discovery and Data Mining Applications, other AI Applications and Short Application Papers.