Variation Based Dense 3D Reconstruction, Sven Painer
Автор: Vivek Bannore Название: Iterative-Interpolation Super-Resolution Image Reconstruction ISBN: 3642101453 ISBN-13(EAN): 9783642101458 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a novel, hybrid, computationally-efficient reconstruction scheme for solving the problem of super-resolution restoration of high-resolution images from sequences of geometrically warped, aliased and under-sampled low-resolution images.
Автор: Mahdi Abdelguerfi Название: 3D Synthetic Environment Reconstruction ISBN: 1461346827 ISBN-13(EAN): 9781461346821 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Giovanni Bellettini; Valentina Beorchia; Maurizio Название: Shape Reconstruction from Apparent Contours ISBN: 3662451905 ISBN-13(EAN): 9783662451908 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Shape Reconstruction from Apparent Contours
Название: Dense image correspondences for computer vision ISBN: 3319230476 ISBN-13(EAN): 9783319230474 Издательство: Springer Рейтинг: Цена: 16979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Dense Image Correspondences for Computer Vision
Автор: Tal Hassner; Ce Liu Название: Dense Image Correspondences for Computer Vision ISBN: 3319359142 ISBN-13(EAN): 9783319359144 Издательство: Springer Рейтинг: Цена: 13059.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation.
Автор: Martin Burger; Andrea C.G. Mennucci; Stanley Osher Название: Level Set and PDE Based Reconstruction Methods in Imaging ISBN: 331901711X ISBN-13(EAN): 9783319017112 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book takes readers on a tour through modern methods in image analysis and reconstruction based on level set and PDE techniques, the major focus being on morphological and geometric structures in images.
This book constitutes the refereed joint proceedings of the International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, the International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017, and the International Stroke Workshop: Imaging and Treatment Challenges, SWITCH 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.
The 5 full papers presented at FIFI 2017, the 9 full papers presented at RAMBO 2017, and the 4 full papers presented at SWITCH 2017 were carefully reviewed and selected. The CMMI papers cover various areas from image synthesis to data analysis and from clinical diagnosis to therapy individualization, using molecular imaging modalities PET, SPECT, PET/CT, SPECT/CT, and PET/MR. The RAMBO papers present research from both academia and industry, They are organized into the categories "registration and tracking" and "image reconstruction and information retrieval" while application areas include cardiac, pulmonal, abdominal, fetal, and renal imaging. The SWITCH papers focus on CT(A)-based quantitative imaging biomarkers for stroke.
Автор: Predrag B. Petrovic; Milorad R. Stevanovic Название: Digital Processing and Reconstruction of Complex Signals ISBN: 3642429254 ISBN-13(EAN): 9783642429255 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book details methods for analyzing, processing and reconstructing complex signals. It presents a newly developed method for the calculation of basic parameters of the processed voltage and current signals.
Описание: This book explores new planar patterns for camera calibration of intrinsic parameters, offering a line-based method for distortion correction. Covers calibration of structured light systems, and 3D Euclidean reconstruction using image-to-world transformation.
Автор: Maria A. Zuluaga; Kanwal Bhatia; Bernhard Kainz; M Название: Reconstruction, Segmentation, and Analysis of Medical Images ISBN: 3319522795 ISBN-13(EAN): 9783319522791 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Registration.- Reconstruction.- Deep learning for heart segmentation.- Discrete optimization and probabilistic intensity modeling.- Atlas-based strategies.- Random forests.
This work is motivated by the ongoing open question of how information in the outside world is represented and processed by the brain. Consequently, several novel methods are developed.
A new mathematical formulation is proposed for the encoding and decoding of analog signals using integrate-and-fire neuron models. Based on this formulation, a novel algorithm, significantly faster than the state-of-the-art method, is proposed for reconstructing the input of the neuron.
Two new identification methods are proposed for neural circuits comprising a filter in series with a spiking neuron model. These methods reduce the number of assumptions made by the state-of-the-art identification framework, allowing for a wider range of models of sensory processing circuits to be inferred directly from input-output observations.
A third contribution is an algorithm that computes the spike time sequence generated by an integrate-and-fire neuron model in response to the output of a linear filter, given the input of the filter encoded with the same neuron model.
Автор: Francesco Bellocchio; N. Alberto Borghese; Stefano Название: 3D Surface Reconstruction ISBN: 1493901176 ISBN-13(EAN): 9781493901173 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 3D Surface Reconstruction: Multi-Scale Hierarchical Approaches presents methods to model 3D objects in an incremental way so as to capture more finer details at each step. Innovative approaches, based on two popular machine learning paradigms, namely Radial Basis Functions and the Support Vector Machines, are also introduced.
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