J de curtò (45 resultados)

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Taschenbuch. Condición: Neu. Fast Kernel Expansions with Applications to CV and DL. Part 1a | Carnegie Mellon. City University of Hong Kong | J. de Curtò | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203925388 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Printed wrappers with flaps, 4to, 26 cm. lx, 172, [1] pp, 64 plates. 194 entrie4s, Covers slightly marked, otherwise a Very Good unopened copy.

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Taschenbuch. Condición: Neu. Vision and Learning in the Context of Exploratory Rovers | ETH Zürich | J. de Curtò | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203924534 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Condición: Neu. Construction and Performance of Network Codes | Universitat Autònoma de Barcelona. Universitat Politècnica de Catalunya | J. de Curtò | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203925012 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

paperback. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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Hardcover. Condición: Fine. No Jacket. 301 pages illustrations 24 cm OCLC 2578209 black cloth no dustjacket ; General contents: Introduction to coin collecting -- Collecting United States coins -- Background of American coinage -- Large and small cents -- Silver dollars -- Other regular issue copper and silver coins -- Gold coins --Commemoratives -- Mint engravers and dies -- Patterns ; FINE. Book.…

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Taschenbuch. Condición: Neu. Sehen und Lernen im Kontext von Exploratory Rovers | ETH Zürich | J. de Curtò | Taschenbuch | 72 S. | Deutsch | 2022 | Verlag Unser Wissen | EAN 9786204895956 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The main aim of the text is to give a review of fast kernel expansions, FOURIER features and rapid numerical code in statistical learning. For this purpose we introduce a library for approximating kernel expansions, which enables the use of kernel methods in datasets with a large number of samples. It is well-known that kernel methods as originally proposed are computational costly for big data, we explain here the theory needed to enable the use of non-linear features in log-linear time. This approximation is based on FOURIER features by the use of the Walsh Hadamard. A SIMD implementation of the algorithm is described. The manuscript contains interesting applications to Computer Vision (CV) and Deep Learning (DL) which can serve as guideline for novel researchers in the topic. In particular we provide a primer on facial recognition and directives for the use of large-scale techniques of Vision in Robotics.The main aim of the text is to give a review of fast kernel expansions, FOURIER features and rapid numerical code in statistical learning. For this purpose we introduce a library for approximating kernel expansions, which enables the use of kernel methods in datasets with a large number of samples. It is well-known that kernel methods as originally proposed are computational costly for big data, we explain here the theory needed to enable the use of non-linear features in log-linear time. This approximation is based on FOURIER features by the use of the Walsh Hadamard. A SIMD implementation of the algorithm is described. The manuscript contains interesting applications to Computer Vision (CV) and Deep Learning (DL) which can serve as guideline for novel researchers in the topic. In particular we provide a primer on facial recognition and directives for the use of large-scale techniques of Vision in Robotics. 88 pp. Englisch.…

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The main goal of this work is to implement and provide a theoretical description of different schemes of Physical-layer Network Coding. Using a basic setup as starting point, the manuscript presents the construction and performance of different systems of communications with increasing complexity. The text is structured in different sections: first, an introduction to Physical-layer Network Coding and Lattice Network Codes is delivered. Next, the mathematical tools required to understand the system of Compute and Forward (C&F) are presented. Further, a first basic scheme is analysed and implemented. The next step consists on implementing a vectorial C&F System and a HAMMING q-ary coded version. Finally, different approaches to improve the matrix of coefficients are studied and implemented.The main goal of this work is to implement and provide a theoretical description of different schemes of Physical-layer Network Coding. Using a basic setup as starting point, the manuscript presents the construction and performance of different systems of communications with increasing complexity. The text is structured in different sections: first, an introduction to Physical-layer Network Coding and Lattice Network Codes is delivered. Next, the mathematical tools required to understand the system of Compute and Forward (C&F) are presented. Further, a first basic scheme is analysed and implemented. The next step consists on implementing a vectorial C&F System and a HAMMING q-ary coded version. Finally, different approaches to improve the matrix of coefficients are studied and implemented. 100 pp. Englisch.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Generative Adversarial Networks (GANs) have had tremendous applications in Computer Vision. Yet, in the context of space science and planetary exploration the door is open for major advances. We introduce tools to handle planetary data from the mission Chang'E-4 and present a framework for Neural Style Transfer using Cycle-consistency from rendered images. We also introduce a new real-time pipeline for Simultaneous Localization and Mapping (SLAM) and Visual Inertial Odometry (VIO) in the context of planetary rovers. We leverage prior information of the location of the lander to propose an object-level SLAM approach that optimizes pose and shape of the lander together with camera trajectories of the rover. As a further refinement step, we propose to use techniques of interpolation between adjacent temporal samples; videlicet synthesizing non-existing images to improve the overall accuracy of the system. The experiments are conducted in the context of the Iris Lunar Rover, a nano-rover that will be deployed in lunar terrain in 2021 as the flagship of Carnegie Mellon, being the first unmanned rover of America to be on the Moon.Generative Adversarial Networks (GANs) have had tremendous applications in Computer Vision. Yet, in the context of space science and planetary exploration the door is open for major advances. We introduce tools to handle planetary data from the mission Chang'E-4 and present a framework for Neural Style Transfer using Cycle-consistency from rendered images. We also introduce a new real-time pipeline for Simultaneous Localization and Mapping (SLAM) and Visual Inertial Odometry (VIO) in the context of planetary rovers. We leverage prior information of the location of the lander to propose an object-level SLAM approach that optimizes pose and shape of the lander together with camera trajectories of the rover. As a further refinement step, we propose to use techniques of interpolation between adjacent temporal samples; videlicet synthesizing non-existing images to improve the overall accuracy of the system. The experiments are conducted in the context of the Iris Lunar Rover, a nano-rover that will be deployed in lunar terrain in 2021 as the flagship of Carnegie Mellon, being the first unmanned rover of America to be on the Moon. 96 pp. Englisch.…

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The main aim of the text is to give a review of fast kernel expansions, FOURIER features and rapid numerical code in statistical learning. For this purpose we introduce a library for approximating kernel expansions, which enables the use of kernel methods in datasets with a large number of samples. It is well-known that kernel methods as originally proposed are computational costly for big data, we explain here the theory needed to enable the use of non-linear features in log-linear time. This approximation is based on FOURIER features by the use of the Walsh Hadamard. A SIMD implementation of the algorithm is described. The manuscript contains interesting applications to Computer Vision (CV) and Deep Learning (DL) which can serve as guideline for novel researchers in the topic. In particular we provide a primer on facial recognition and directives for the use of large-scale techniques of Vision in Robotics.The main aim of the text is to give a review of fast kernel expansions, FOURIER features and rapid numerical code in statistical learning. For this purpose we introduce a library for approximating kernel expansions, which enables the use of kernel methods in datasets with a large number of samples. It is well-known that kernel methods as originally proposed are computational costly for big data, we explain here the theory needed to enable the use of non-linear features in log-linear time. This approximation is based on FOURIER features by the use of the Walsh Hadamard. A SIMD implementation of the algorithm is described. The manuscript contains interesting applications to Computer Vision (CV) and Deep Learning (DL) which can serve as guideline for novel researchers in the topic. In particular we provide a primer on facial recognition and directives for the use of large-scale techniques of Vision in Robotics.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Las redes generativas antagónicas (GAN) han tenido tremendas aplicaciones en visión artificial. Sin embargo, en el contexto de la ciencia espacial y la exploración planetaria, la puerta está abierta para avances importantes. Presentamos herramientas para manejar datos planetarios de la misión Chang'E-4 y presentamos un marco para la transferencia de estilo neuronal utilizando la coherencia de ciclo de imágenes renderizadas. También presentamos una nueva canalización en tiempo real para localización y mapeo simultáneos (SLAM) y odometría inercial visual (VIO) en el contexto de los rovers planetarios. Aprovechamos la información previa de la ubicación del módulo de aterrizaje para proponer un enfoque SLAM a nivel de objeto que optimiza la pose y la forma del módulo de aterrizaje junto con las trayectorias de la cámara del rover. Como paso de perfeccionamiento adicional, proponemos utilizar técnicas de interpolación entre muestras temporales adyacentes; videlicet sintetiza imágenes inexistentes para mejorar la precisión general del sistema. Los experimentos se realizan en el contexto del Iris Lunar Rover, un nano-rover que se desplegará en terreno lunar en 2021 como buque insignia de Carnegie Mellon, siendo el primer rover no tripulado de América en pisar la Luna. 72 pp. Spanisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Generative Adversarial Networks (GANs) have had tremendous applications in Computer Vision. Yet, in the context of space science and planetary exploration the door is open for major advances. We introduce tools to handle planetary data from the mission Chang'E-4 and present a framework for Neural Style Transfer using Cycle-consistency from rendered images. We also introduce a new real-time pipeline for Simultaneous Localization and Mapping (SLAM) and Visual Inertial Odometry (VIO) in the context of planetary rovers. We leverage prior information of the location of the lander to propose an object-level SLAM approach that optimizes pose and shape of the lander together with camera trajectories of the rover. As a further refinement step, we propose to use techniques of interpolation between adjacent temporal samples; videlicet synthesizing non-existing images to improve the overall accuracy of the system. The experiments are conducted in the context of the Iris Lunar Rover, a nano-rover that will be deployed in lunar terrain in 2021 as the flagship of Carnegie Mellon, being the first unmanned rover of America to be on the Moon.Generative Adversarial Networks (GANs) have had tremendous applications in Computer Vision. Yet, in the context of space science and planetary exploration the door is open for major advances. We introduce tools to handle planetary data from the mission Chang'E-4 and present a framework for Neural Style Transfer using Cycle-consistency from rendered images. We also introduce a new real-time pipeline for Simultaneous Localization and Mapping (SLAM) and Visual Inertial Odometry (VIO) in the context of planetary rovers. We leverage prior information of the location of the lander to propose an object-level SLAM approach that optimizes pose and shape of the lander together with camera trajectories of the rover. As a further refinement step, we propose to use techniques of interpolation between adjacent temporal samples; videlicet synthesizing non-existing images to improve the overall accuracy of the system. The experiments are conducted in the context of the Iris Lunar Rover, a nano-rover that will be deployed in lunar terrain in 2021 as the flagship of Carnegie Mellon, being the first unmanned rover of America to be on the Moon.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The main goal of this work is to implement and provide a theoretical description of different schemes of Physical-layer Network Coding. Using a basic setup as starting point, the manuscript presents the construction and performance of different systems of communications with increasing complexity. The text is structured in different sections: first, an introduction to Physical-layer Network Coding and Lattice Network Codes is delivered. Next, the mathematical tools required to understand the system of Compute and Forward (C&F) are presented. Further, a first basic scheme is analysed and implemented. The next step consists on implementing a vectorial C&F System and a HAMMING q-ary coded version. Finally, different approaches to improve the matrix of coefficients are studied and implemented.The main goal of this work is to implement and provide a theoretical description of different schemes of Physical-layer Network Coding. Using a basic setup as starting point, the manuscript presents the construction and performance of different systems of communications with increasing complexity. The text is structured in different sections: first, an introduction to Physical-layer Network Coding and Lattice Network Codes is delivered. Next, the mathematical tools required to understand the system of Compute and Forward (C&F) are presented. Further, a first basic scheme is analysed and implemented. The next step consists on implementing a vectorial C&F System and a HAMMING q-ary coded version. Finally, different approaches to improve the matrix of coefficients are studied and implemented.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The main aim of the text is to give a review of fast kernel expansions, FOURIER features and rapid numerical code in statistical learning. For this purpose we introduce a library for approximating kernel expansions, which enables the use of kernel methods in datasets with a large number of samples. It is well-known that kernel methods as originally proposed are computational costly for big data, we explain here the theory needed to enable the use of non-linear features in log-linear time. This approximation is based on FOURIER features by the use of the Walsh Hadamard. A SIMD implementation of the algorithm is described. The manuscript contains interesting applications to Computer Vision (CV) and Deep Learning (DL) which can serve as guideline for novel researchers in the topic. In particular we provide a primer on facial recognition and directives for the use of large-scale techniques of Vision in Robotics.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Les réseaux antagonistes génératifs (GAN) ont eu d'énormes applications dans la vision par ordinateur. Pourtant, dans le contexte des sciences spatiales et de l'exploration planétaire, la porte est ouverte à des avancées majeures. Nous introduisons des outils pour gérer les données planétaires de la mission Chang'E-4 et présentons un cadre pour le transfert de style neuronal utilisant la cohérence cyclique à partir d'images rendues. Nous introduisons également un nouveau pipeline en temps réel pour la localisation et la cartographie simultanées (SLAM) et l'odométrie inertielle visuelle (VIO) dans le contexte des rovers planétaires. Nous tirons parti des informations préalables sur l'emplacement de l'atterrisseur pour proposer une approche SLAM au niveau de l'objet qui optimise la pose et la forme de l'atterrisseur ainsi que les trajectoires de caméra du rover. Comme étape de raffinement supplémentaire, nous proposons d'utiliser des techniques d'interpolation entre échantillons temporels adjacents ; videlicet synthétisant des images inexistantes pour améliorer la précision globale du système. Les expériences sont menées dans le cadre de l'Iris Lunar Rover, un nano-rover qui sera déployé sur le terrain lunaire en 2021 en tant que vaisseau amiral de Carnegie Mellon, étant le premier rover sans pilote d'Amérique à être sur la Lune. 72 pp. Französisch.…