Findler michael (40 Ergebnisse)

Sprache: Englisch
Verlag: The British Library Publishing Division, 2015
- Softcover
Anbieter: Chiron Media, Wallingford, Vereinigtes KönigreichChiron Media
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Sprache: Englisch
Verlag: The British Library Publishing Division 2015-04-01, 2015
- Softcover
Anbieter: Chiron Media, Wallingford, Vereinigtes KönigreichChiron Media
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Paperback. Zustand: New.

Intelligent Autonomous Drones with Cognitive Deep Learning: Build AI-Enabled Land Drones with the Raspberry Pi 4
Sears, Benjamin,Harbour, Steven D.,Blubaugh, David Allen,Findler, Michael J.
- Softcover
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paperback. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Intelligent Autonomous Drones With Cognitive Deep Learning : Build Ai-enabled Land Drones With the Raspberry Pi 4
Blubaugh, David Allen; Sears, Benjamin; Harbour, Steven D.; Findler, Michael J.
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Intelligent Autonomous Drones With Cognitive Deep Learning : Build Ai-enabled Land Drones With the Raspberry Pi 4
Blubaugh, David Allen; Sears, Benjamin; Harbour, Steven D.; Findler, Michael J.
- Softcover
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Intelligent Autonomous Drones with Cognitive Deep Learning
Michael J. Findler, David Allen Blubaugh, Steven D. Harbour, Benjamin Sears
- Softcover
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Paperback. Zustand: New. What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone.You'll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards established by for the Robotic Operating System (ROS). The ROS architecture has been used to develop land-based drones. This will serve as a reference model for the software architecture of unmanned systems. Using this approach you'll be able to develop a fully autonomous drone that incorporates object-oriented design and cognitive deep learning systems that adapts to multiple simulation environments. These multiple simulation environments will also allow you to further build public trust in the safety of artificial intelligence within drones and small UAS. Ultimately, you'll be able to build a complex system using the standards developed, and create other intelligent systems of similar complexity and capability.Intelligent Autonomous Drones with Cognitive Deep Learning uniquely addresses both deep learning and cognitive deep learning for developing near autonomous drones.What You'll LearnExamine the necessary specifications and requirements for AI enabled drones for near-real time and near fully autonomous dronesLook at software and hardware requirementsUnderstand unified modeling language (UML) and real-time UML for designStudy deep learning neural networks for pattern recognitionReview geo-spatial Information for the development of detailed mission planning within these hostile environmentsWho This Book IsForPrimarily for engineers, computer science graduate students, or even a skilled hobbyist. The target readers have the willingness to learn and extend the topic of intelligent autonomous drones. They should have a willingness to explore exciting engineering projects that are limited only by their imagination. As far as the technical requirements are concerned, they must have an intermediate understanding of object-oriented programming and design.…

Intelligent Autonomous Drones with Cognitive Deep Learning: Build AI-Enabled Land Drones with the Raspberry Pi 4
Blubaugh, David Allen; Harbour, Steven D.; Sears, Benjamin; Findler, Michael J.
- Softcover
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Intelligent Autonomous Drones with Cognitive Deep Learning: Build AI-Enabled Land Drones with the Raspberry Pi 4
Blubaugh, David Allen, Harbour, Steven D., Sears, Benjamin, Findler, Michael J.
Verlag: Apress
- Softcover
Anbieter: Academic Book Solutions, Medford, NY, USAAcademic Book Solutions
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In den WarenkorbPaperback. Zustand: Good. A copy that may have been read, minimal to no highlighting/underlining of text, no missing pages. May have a remainder mark. Spine may show signs of wear. Could be a library copy.

Intelligent Autonomous Drones with Cognitive Deep Learning
Michael J. Findler, David Allen Blubaugh, Steven D. Harbour, Benjamin Sears
- Softcover
Anbieter: Rarewaves.com USA, London, LONDO, Vereinigtes KönigreichRarewaves.com USA
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Paperback. Zustand: New. What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone.You'll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards established by for the Robotic Operating System (ROS). The ROS architecture has been used to develop land-based drones. This will serve as a reference model for the software architecture of unmanned systems. Using this approach you'll be able to develop a fully autonomous drone that incorporates object-oriented design and cognitive deep learning systems that adapts to multiple simulation environments. These multiple simulation environments will also allow you to further build public trust in the safety of artificial intelligence within drones and small UAS. Ultimately, you'll be able to build a complex system using the standards developed, and create other intelligent systems of similar complexity and capability.Intelligent Autonomous Drones with Cognitive Deep Learning uniquely addresses both deep learning and cognitive deep learning for developing near autonomous drones.What You'll LearnExamine the necessary specifications and requirements for AI enabled drones for near-real time and near fully autonomous dronesLook at software and hardware requirementsUnderstand unified modeling language (UML) and real-time UML for designStudy deep learning neural networks for pattern recognitionReview geo-spatial Information for the development of detailed mission planning within these hostile environmentsWho This Book IsForPrimarily for engineers, computer science graduate students, or even a skilled hobbyist. The target readers have the willingness to learn and extend the topic of intelligent autonomous drones. They should have a willingness to explore exciting engineering projects that are limited only by their imagination. As far as the technical requirements are concerned, they must have an intermediate understanding of object-oriented programming and design.…

Intelligent Autonomous Drones with Cognitive Deep
Blubaugh, David Allen; Harbour, Steven D.; Sears, Benjamin; Findler, Michael J.
- Softcover
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Intelligent Autonomous Drones with Cognitive Deep
Blubaugh, David Allen; Harbour, Steven D.; Sears, Benjamin; Findler, Michael J.
- Softcover
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Intelligent Autonomous Drones with Cognitive Deep Learning: Build AI-Enabled Land Drones with the Raspberry Pi 4
Blubaugh, David Allen; Harbour, Steven D.; Sears, Benjamin; Findler, Michael J.
- Softcover
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Intelligent Autonomous Drones with Cognitive Deep Learning: Build AI-Enabled Land Drones with the Raspberry Pi 4
Blubaugh, David Allen; Harbour, Steven D.; Sears, Benjamin; Findler, Michael J.
- Softcover
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Intelligent Autonomous Drones With Cognitive Deep Learning : Build Ai-enabled Land Drones With the Raspberry Pi 4
Blubaugh, David Allen; Sears, Benjamin; Harbour, Steven D.; Findler, Michael J.
- Softcover
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Intelligent Autonomous Drones with Cognitive Deep Learning: Build AI-Enabled Land Drones with the Raspberry Pi 4
Blubaugh, David Allen; Harbour, Steven D.; Sears, Benjamin; Findler, Michael J.
- Softcover
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Intelligent Autonomous Drones With Cognitive Deep Learning : Build Ai-enabled Land Drones With the Raspberry Pi 4
Blubaugh, David Allen; Sears, Benjamin; Harbour, Steven D.; Findler, Michael J.
- Softcover
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Revised [6] Report On The Algorithmic Language Scheme
Michael Cummings Peter Fries William C. Spruiell,David Lockwood,,
- Hardcover
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Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

- Hardcover
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Intelligent Autonomous Drones With Cognitive Deep Learning: Build Ai-enabled Land Drones With the Raspberry Pi 4
Blubaugh, David Allen/ Sears, Benjamin/ Harbour, Steven D./ Findler, Michael J.
- Softcover
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Paperback. Zustand: Brand New. 527 pages. 9.25x6.10x1.06 inches. In Stock.

Intelligent Autonomous Drones with Cognitive Deep Learning: Build AI-Enabled Land Drones with the Raspberry Pi 4
Blubaugh, David Allen; Harbour, Steven D.; Sears, Benjamin; Findler, Michael J.
- Softcover
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Intelligent Autonomous Drones with Cognitive Deep Learning
Michael J. Findler, David Allen Blubaugh, Steven D. Harbour, Benjamin Sears
- Softcover
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Paperback. Zustand: New. What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone.You'll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards established by for the Robotic Operating System (ROS). The ROS architecture has been used to develop land-based drones. This will serve as a reference model for the software architecture of unmanned systems. Using this approach you'll be able to develop a fully autonomous drone that incorporates object-oriented design and cognitive deep learning systems that adapts to multiple simulation environments. These multiple simulation environments will also allow you to further build public trust in the safety of artificial intelligence within drones and small UAS. Ultimately, you'll be able to build a complex system using the standards developed, and create other intelligent systems of similar complexity and capability.Intelligent Autonomous Drones with Cognitive Deep Learning uniquely addresses both deep learning and cognitive deep learning for developing near autonomous drones.What You'll LearnExamine the necessary specifications and requirements for AI enabled drones for near-real time and near fully autonomous dronesLook at software and hardware requirementsUnderstand unified modeling language (UML) and real-time UML for designStudy deep learning neural networks for pattern recognitionReview geo-spatial Information for the development of detailed mission planning within these hostile environmentsWho This Book IsForPrimarily for engineers, computer science graduate students, or even a skilled hobbyist. The target readers have the willingness to learn and extend the topic of intelligent autonomous drones. They should have a willingness to explore exciting engineering projects that are limited only by their imagination. As far as the technical requirements are concerned, they must have an intermediate understanding of object-oriented programming and design.…

- Hardcover
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Zustand: Used. pp. 302 6th Revised Edition.

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Report on the Algorithmic Language Scheme
Straaten Anton van Flatt Matthew Dybvig R. Kent Sperber Michael
- Hardcover
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Report on the Algorithmic Language Scheme
Sperber, Michael (EDT); Dybvig, R. Kent (EDT); Flatt, Matthew (EDT); Van Straaten, Anton (EDT)
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Intelligent Autonomous Drones with Cognitive Deep Learning
Michael J. Findler, David Allen Blubaugh, Steven D. Harbour, Benjamin Sears
- Softcover
Anbieter: Rarewaves.com UK, London, Vereinigtes KönigreichRarewaves.com UK
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Paperback. Zustand: New. What is an artificial intelligence (AI)-enabled drone and what can it do? Are AI-enabled drones better than human-controlled drones? This book will answer these questions and more, and empower you to develop your own AI-enabled drone.You'll progress from a list of specifications and requirements, in small and iterative steps, which will then lead to the development of Unified Modeling Language (UML) diagrams based in part to the standards established by for the Robotic Operating System (ROS). The ROS architecture has been used to develop land-based drones. This will serve as a reference model for the software architecture of unmanned systems. Using this approach you'll be able to develop a fully autonomous drone that incorporates object-oriented design and cognitive deep learning systems that adapts to multiple simulation environments. These multiple simulation environments will also allow you to further build public trust in the safety of artificial intelligence within drones and small UAS. Ultimately, you'll be able to build a complex system using the standards developed, and create other intelligent systems of similar complexity and capability.Intelligent Autonomous Drones with Cognitive Deep Learning uniquely addresses both deep learning and cognitive deep learning for developing near autonomous drones.What You'll LearnExamine the necessary specifications and requirements for AI enabled drones for near-real time and near fully autonomous dronesLook at software and hardware requirementsUnderstand unified modeling language (UML) and real-time UML for designStudy deep learning neural networks for pattern recognitionReview geo-spatial Information for the development of detailed mission planning within these hostile environmentsWho This Book IsForPrimarily for engineers, computer science graduate students, or even a skilled hobbyist. The target readers have the willingness to learn and extend the topic of intelligent autonomous drones. They should have a willingness to explore exciting engineering projects that are limited only by their imagination. As far as the technical requirements are concerned, they must have an intermediate understanding of object-oriented programming and design.…

- Hardcover
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Zustand: New. In English.

Report on the Algorithmic Language Scheme
Sperber, Michael (EDT); Dybvig, R. Kent (EDT); Flatt, Matthew (EDT); Van Straaten, Anton (EDT)
- Hardcover
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- Hardcover
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Zustand: New. A series of reports describing the innovative programming language Scheme. Editor(s): Sperber, Michael; Dybvig, R.Kent; Flatt, Matthew; Straaten, Anton Van; Findler, Robby; Matthews, Jacob. Num Pages: 302 pages. BIC Classification: UMB; UYA. Category: (P) Professional & Vocational. Dimension: 257 x 182 x 18. Weight in Grams: 680. . 2010. New. hardcover. . . . . …