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Author: Howard Weinstein
Publisher: Simon and Schuster
ISBN: 0743419847
Category : Fiction
Languages : en
Pages : 434
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Book Description
Deep Domain A routine diplomatic visit to the water-world of Akkalla becomes a nightmarish search for a missing Spock and Chekov, a search that plunges Admiral Kirk headlong into a corrupt government's desperate struggle to retain power. For both A Federation Science outpost and Akkalla's valiant freedom fighters have begun uncovering the ancient secrets hidden beneath her tranquil oceans. Secrets whose exposure may even mean civil war for the people of Akkalla -- and death for the crew of the Starship Enterprise™.
Author: Howard Weinstein
Publisher: Simon and Schuster
ISBN: 0743419847
Category : Fiction
Languages : en
Pages : 434
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Book Description
Deep Domain A routine diplomatic visit to the water-world of Akkalla becomes a nightmarish search for a missing Spock and Chekov, a search that plunges Admiral Kirk headlong into a corrupt government's desperate struggle to retain power. For both A Federation Science outpost and Akkalla's valiant freedom fighters have begun uncovering the ancient secrets hidden beneath her tranquil oceans. Secrets whose exposure may even mean civil war for the people of Akkalla -- and death for the crew of the Starship Enterprise™.
Author: Howard Weinstein
Publisher: Star Trek
ISBN: 9780671705497
Category : Missing persons
Languages : en
Pages : 0
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Book Description
A routine diplomatic visit to the water-world of Akkalla becomes a nightmarish search for a missing Spock and Chekov. The search plunges Admiral Kirk into a corrupt government's desperate struggle to retain power.
Author: Gustau Camps-Valls
Publisher: John Wiley & Sons
ISBN: 1119646162
Category : Technology & Engineering
Languages : en
Pages : 436
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Book Description
DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.
Author: Hemanth Venkateswara
Publisher: Springer Nature
ISBN: 3030455297
Category : Computers
Languages : en
Pages : 258
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Book Description
This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation. Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation. This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.
Author: Dominic Walliman
Publisher:
ISBN: 9781912497126
Category : Ocean
Languages : en
Pages : 69
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Book Description
Where did the oceans come from? Can you take a submarine to the bottom of the sea? What exactly is a coral reef? Learn about ocean creatures big and small, and how humans explore the underwater world in this incredible illustrated book on the depths of the sea. Join your helpful guide, Professor Astro Cat, as he takes a dive from the seashore all the way to the ocean floor. From whales to deep-sea vents, there's so much to discover on this Deep-Sea Voyage.
Author: James Herbert
Publisher: Pan Macmillan
ISBN: 1447203380
Category : Fiction
Languages : en
Pages : 444
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Book Description
Apocalyptic survival at its most terrifying. The third in the Rats trilogy, international bestseller James Herbert's Domain pits man against mutant rats, who are back with a vengeance. The long-dreaded nuclear conflict. The city torn apart, shattered, its people destroyed or mutilated beyond hope. For just a few, survival is possible only beneath the wrecked streets – if there is time to avoid the slow-descending poisonous ashes. But below, the rats, demonic offspring of their irradiated forebears, are waiting. They know that Man is weakened, become frail. Has become their prey . . . Start the Master of Horror's chilling series from the beginning with The Rats and Lair.
Author: Eric Evans
Publisher: Addison-Wesley Professional
ISBN: 0321125215
Category : Computers
Languages : en
Pages : 563
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Book Description
"Domain-Driven Design" incorporates numerous examples in Java-case studies taken from actual projects that illustrate the application of domain-driven design to real-world software development.
Author: Gabriela Csurka
Publisher: Springer
ISBN: 3319583476
Category : Computers
Languages : en
Pages : 338
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Book Description
This comprehensive text/reference presents a broad review of diverse domain adaptation (DA) methods for machine learning, with a focus on solutions for visual applications. The book collects together solutions and perspectives proposed by an international selection of pre-eminent experts in the field, addressing not only classical image categorization, but also other computer vision tasks such as detection, segmentation and visual attributes. Topics and features: surveys the complete field of visual DA, including shallow methods designed for homogeneous and heterogeneous data as well as deep architectures; presents a positioning of the dataset bias in the CNN-based feature arena; proposes detailed analyses of popular shallow methods that addresses landmark data selection, kernel embedding, feature alignment, joint feature transformation and classifier adaptation, or the case of limited access to the source data; discusses more recent deep DA methods, including discrepancy-based adaptation networks and adversarial discriminative DA models; addresses domain adaptation problems beyond image categorization, such as a Fisher encoding adaptation for vehicle re-identification, semantic segmentation and detection trained on synthetic images, and domain generalization for semantic part detection; describes a multi-source domain generalization technique for visual attributes and a unifying framework for multi-domain and multi-task learning. This authoritative volume will be of great interest to a broad audience ranging from researchers and practitioners, to students involved in computer vision, pattern recognition and machine learning.
Author: Huazhu Fu
Publisher: Springer Nature
ISBN: 3030870006
Category : Computers
Languages : en
Pages : 211
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Book Description
This book constitutes the refereed proceedings of the 8th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2021, held in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in September 2021.* The 20 papers presented at OMIA 2021 were carefully reviewed and selected from 31 submissions. The papers cover various topics in the field of ophthalmic medical image analysis and challenges in terms of reliability and validation, number and type of conditions considered, multi-modal analysis (e.g., fundus, optical coherence tomography, scanning laser ophthalmoscopy), novel imaging technologies, and the effective transfer of advanced computer vision and machine learning technologies. *The workshop was held virtually.
Author: Christian S. Jensen
Publisher: Springer Nature
ISBN: 3030731979
Category : Computers
Languages : en
Pages : 801
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Book Description
The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.
