P v arun kumar (81 resultados)

Condición: New.

Condición: New.

Taschenbuch. Condición: Neu. Statistical Downscaling of Climatic parameters | Forecasting regional scale Rainfall and Temperature using Statistical Downscaling model under various climatic scenarios | P. V. Arun Kumar (u. a.) | Taschenbuch | 72 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202552073 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Paperback. Condición: Brand New. 174 pages. 6.14x0.39x9.21 inches. In Stock.

hardcover. Condición: Fine.

Taschenbuch. Condición: Neu. Neuware - With rapid advancements in AI, this book reveals how AI can be a powerful tool in reducing pollution and fostering sustainability. It highlights the integration of geospatial techniques with AI for enhancing capabilities in mapping, analysis, and mitigation of environmental pollution. Starting with foundational concepts in AI, geospatial technology, and pollution, the book addresses air, water, soil and thermal pollution, emphasizing their harmful impacts. Through real-world case studies and advanced research, it showcases AI and geospatial technology's revolutionary role in pollution mitigation, exploring AI-driven sensors, satellite imagery, and associated networks for precise and efficient pollution monitoring and management.…

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

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Condición: New.

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Hardback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: As New. Unread book in perfect condition.

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Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New. 1st edition NO-PA16APR2015-KAP.

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Hardback. Condición: New. New copy - Usually dispatched within 4 working days.

Hardback. Condición: New. The role of artificial intelligence is crucial in the domain of Earth Observation (EO) data analysis. Deep learning-based approaches have improved accuracy, but they have affected the reliability and transparency of EO data. It is critical to improve the explainability of EO data analysis algorithms and complex deep learning models to ensure the quality of spatial decisions. This book discusses the various advancements in Explainable AI and investigates their suitability for various EO data analyses offering best practices for implementing algorithms that facilitate big and efficient data processing. It lays the foundation of Explainable EO and helps readers build trustworthy, secure, and robust EO systems.Features:Examines explainability of algorithms from the aspect of generalizability and reliabilityReviews state-of-the-art explainability strategies related to the preprocessing algorithmsProvides explanations for specific evaluation metrics of various EO data processing and preprocessing algorithmsDiscusses explainable ante-hoc and post-hoc approaches for EO data analysisServes as a foundational reference for developing future EO data processing strategiesAddresses the key challenges in making EO data processing algorithms interpretable and offers insights for the future of explainable EO data processingThis book is intended for graduate students, researchers and academics in computer and data science, machine learning, and image processing, as well as professionals in geospatial data science using GIS and remote sensing in Earth and environmental sciences.…

Condición: New.

Condición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Hardcover. Condición: Brand New. 320 pages. 9.18x6.12x9.21 inches. In Stock.

Hardback. Condición: New. With rapid advancements in AI, this book reveals how AI can be a powerful tool in reducing pollution and fostering sustainability. It highlights the integration of geospatial techniques with AI for enhancing capabilities in mapping, analysis, and mitigation of environmental pollution. Starting with foundational concepts in AI, geospatial technology, and pollution, the book addresses air, water, soil and thermal pollution, emphasizing their harmful impacts. Through real-world case studies and advanced research, it showcases AI and geospatial technology's revolutionary role in pollution mitigation, exploring AI-driven sensors, satellite imagery, and associated networks for precise and efficient pollution monitoring and management.…

Condición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Hardcover. Condición: Brand New. 182 pages. 9.19x6.13x9.21 inches. In Stock.

Hardback. Condición: New. The role of artificial intelligence is crucial in the domain of Earth Observation (EO) data analysis. Deep learning-based approaches have improved accuracy, but they have affected the reliability and transparency of EO data. It is critical to improve the explainability of EO data analysis algorithms and complex deep learning models to ensure the quality of spatial decisions. This book discusses the various advancements in Explainable AI and investigates their suitability for various EO data analyses offering best practices for implementing algorithms that facilitate big and efficient data processing. It lays the foundation of Explainable EO and helps readers build trustworthy, secure, and robust EO systems.Features:Examines explainability of algorithms from the aspect of generalizability and reliabilityReviews state-of-the-art explainability strategies related to the preprocessing algorithmsProvides explanations for specific evaluation metrics of various EO data processing and preprocessing algorithmsDiscusses explainable ante-hoc and post-hoc approaches for EO data analysisServes as a foundational reference for developing future EO data processing strategiesAddresses the key challenges in making EO data processing algorithms interpretable and offers insights for the future of explainable EO data processingThis book is intended for graduate students, researchers and academics in computer and data science, machine learning, and image processing, as well as professionals in geospatial data science using GIS and remote sensing in Earth and environmental sciences.…