Artificial intelligence digital image (23 résultats)

Paperback. Etat : Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Adcock, Victor Scott (illustrateur).

paperback. Etat : Very Good. Adcock, Victor Scott (illustrateur).

paperback. Etat : Fine. Adcock, Victor Scott (illustrateur).

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Etat : New.

Etat : New. In English.

Paperback. Etat : New.

Taschenbuch. Etat : Neu. Artificial Neural Networks Applied For Digital Images with Matlab Code | The Applications of Artificial Intelligence In Image Processing Field Using Matlab | Muhammad Atta Othman A. Khfagy | Taschenbuch | 152 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659538179 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.…

Hardcover. Etat : new. Hardcover. This book is a focused, practice-driven resource organized around 10 key thematic sections, blending foundational AI knowledge with cutting-edge digital image processing applicationsideal for bridging theory and real-world use. It avoids generic coverage, instead diving into specialized, high-demand topics like deep learning fundamentals, deepfake technology, adversarial attacks in computer vision, adaptive cryptography, and generative AI-driven SAR-to-optical image translation. As a postgraduate handbook, it aligns perfectly with courses such as AI Image Processing, Advanced Signal Processing, and Optical Information Security, helping students grasp core concepts (e.g., Q-learning for cancer detection-related image segmentation, deep learning-based remote sensing classification) and build practical skills.Beyond academia, it caters to a broad range of users: researchers and faculty gain insights into novel directions like secure image processing via optical cryptography and automated dataset generation (SciData-Factory), while industry professionals in remote sensing (secure data handling with dynamic optical transforms), cybersecurity (adversarial defense), and medical imaging (AI-aided cancer detection) find actionable solutions for real-world challenges. Self-learners and career changers benefit from its foundational content and coverage of in-demand skills (aligned with certifications like IEEE Signal Processing), and educational institutions or corporate L&D programs (tech, aerospace, healthcare) can adopt it for upskilling. Supplementary online resourcesincluding topic-specific code and lecture slidesadd further value, making the book essential for anyone working in AI-driven image processing. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Etat : New.

Hardcover. Etat : Brand New. 286 pages. 6.30x0.87x9.49 inches. In Stock.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a focused, practice-driven resource organized around 10 key thematic sections, blending foundational AI knowledge with cutting-edge digital image processing applications ideal for bridging theory and real-world use. It avoids generic coverage, instead diving into specialized, high-demand topics like deep learning fundamentals, deepfake technology, adversarial attacks in computer vision, adaptive cryptography, and generative AI-driven SAR-to-optical image translation. As a postgraduate handbook, it aligns perfectly with courses such as AI Image Processing, Advanced Signal Processing, and Optical Information Security, helping students grasp core concepts (e.g., Q-learning for cancer detection-related image segmentation, deep learning-based remote sensing classification) and build practical skills.Beyond academia, it caters to a broad range of users: researchers and faculty gain insights into novel directions like secure image processing via optical cryptography and automated dataset generation (SciData-Factory), while industry professionals in remote sensing (secure data handling with dynamic optical transforms), cybersecurity (adversarial defense), and medical imaging (AI-aided cancer detection) find actionable solutions for real-world challenges. Self-learners and career changers benefit from its foundational content and coverage of in-demand skills (aligned with certifications like IEEE Signal Processing), and educational institutions or corporate L&D programs (tech, aerospace, healthcare) can adopt it for upskilling. Supplementary online resources including topic-specific code and lecture slides add further value, making the book essential for anyone working in AI-driven image processing. …

Hardcover. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

paperback. Etat : New. Language:Chinese.Paperback. Pub Date: 2021-10-01 Pages: 492 Publisher: Tsinghua University Press This book is based on the current development of artificial intelligence RNN deep learning. a specific design based on the RNN model algorithm. and the specific implementation. z new algorithm Process and Python code implementation.?Its main content includes: 20 cases of image processing based on deep learning. specific implementation based on Python. this book is rich in illustrations and texts. .…

PAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial Neural Networks have broad applications to the real world business problems. They have already been successfully applied in many industries. Since neural networks are best at identifying patterns or trends in data, they are well suited for prediction or forecasting. These include Sales forecasting, Industrial process control, Customer research, Data validation, Risk management, Target marketing. The work studies the use of Artificial Neural Network in the field of Image Processing. One of the applications studied is the edge detection process. Edge detection of an image significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. Edges detection of digital images is used in a various fields of applications ranging from real-time video surveillance and traffic management to medical imaging applications. The work demonstrates both entropy and Neural Network based edge detection methods, where Renyi s Entropy and Convolutional Neural Network based edge detection is proposed and their results are compared.…

Taschenbuch. Etat : Neu. Computer Vision | Artificial intelligence, Strong AI, Digital image processing, Image processing, List of computer vision topics, Machine learning, Machine vision, Glossary of machine vision, Medical imaging | Frederic P. Miller (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786130201395 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a focused, practice-driven resource organized around 10 key thematic sections, blending foundational AI knowledge with cutting-edge digital image processing applications ideal for bridging theory and real-world use. It avoids generic coverage, instead diving into specialized, high-demand topics like deep learning fundamentals, deepfake technology, adversarial attacks in computer vision, adaptive cryptography, and generative AI-driven SAR-to-optical image translation. As a postgraduate handbook, it aligns perfectly with courses such as AI Image Processing, Advanced Signal Processing, and Optical Information Security, helping students grasp core concepts (e.g., Q-learning for cancer detection-related image segmentation, deep learning-based remote sensing classification) and build practical skills.Beyond academia, it caters to a broad range of users: researchers and faculty gain insights into novel directions like secure image processing via optical cryptography and automated dataset generation (SciData-Factory), while industry professionals in remote sensing (secure data handling with dynamic optical transforms), cybersecurity (adversarial defense), and medical imaging (AI-aided cancer detection) find actionable solutions for real-world challenges. Self-learners and career changers benefit from its foundational content and coverage of in-demand skills (aligned with certifications like IEEE Signal Processing), and educational institutions or corporate L&D programs (tech, aerospace, healthcare) can adopt it for upskilling. Supplementary online resources including topic-specific code and lecture slides add further value, making the book essential for anyone working in AI-driven image processing. 276 pp. Englisch.…

Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is a focused, practice-driven resource organized around 10 key thematic sections, blending foundational AI knowledge with cutting-edge digital image processing applicationsideal for bridging theory and real-world use. It avoids generic coverage, instead diving into specialized, high-demand topics like deep learning fundamentals, deepfake technology, adversarial attacks in computer vision, adaptive cryptography, and generative AI-driven SAR-to-optical image translation. As a postgraduate handbook, it aligns perfectly with courses such as "AI Image Processing," "Advanced Signal Processing," and "Optical Information Security," helping students grasp core concepts (e.g., Q-learning for cancer detection-related image segmentation, deep learning-based remote sensing classification) and build practical skills.Beyond academia, it caters to a broad range of users: researchers and faculty gain insights into novel directions like secure image processing via optical cryptography and automated dataset generation (SciData-Factory), while industry professionals in remote sensing (secure data handling with dynamic optical transforms), cybersecurity (adversarial defense), and medical imaging (AI-aided cancer detection) find actionable solutions for real-world challenges. Self-learners and career changers benefit from its foundational content and coverage of in-demand skills (aligned with certifications like IEEE Signal Processing), and educational institutions or corporate L&D programs (tech, aerospace, healthcare) can adopt it for upskilling. Supplementary online resourcesincluding topic-specific code and lecture slidesadd further value, making the book essential for anyone working in AI-driven image processing.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 288 pp. Englisch.…

Etat : New. Print on Demand.

Etat : New. PRINT ON DEMAND.