Songs of the Royal Zhou and the Royal Shao: Shi ? of the Anhui University Manuscripts, Adam Craig Schwartz, Dirk Meyer
Автор: Sherwood Shirley Название: Shirley Sherwood Collection ISBN: 1842466933 ISBN-13(EAN): 9781842466933 Издательство: Marston Book Services Рейтинг: Цена: 5544.00 р. Наличие на складе: Ожидается поступление.
Описание: This book is a celebration of the Shirley Sherwood Collection of contemporary botanical art, made over a period of 30 years by Dr Shirley Sherwood and considered the most important private collection of its kind in the world.
Автор: Sherwood Shirley, Rix Martyn Название: Treasures of Botanical Art ISBN: 1842466631 ISBN-13(EAN): 9781842466636 Издательство: Marston Book Services Рейтинг: Цена: 3168.00 р. Наличие на складе: Ожидается поступление.
Описание: Treasures of Botanical Art reveals the history of botanical painting, its beauty and science, with works from two renowned collections and over one hundred significant artists, dating from the late 1400s through to today.
Описание: This book studies selected discrete-time flight control schemes for fixed-wing unmanned aerial vehicle (UAV) systems in the presence of system uncertainties, external disturbances and input saturation.
4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (LABELS 2019).- Comparison of active learning strategies applied to lung nodule segmentation in CT scans.- Robust Registration of Statistical Shape Models for Unsupervised Pathology Annotation.- XiangyaDerm: A Clinical Image Dataset of Asian Race for Skin Disease Aided Diagnosis.- Data Augmentation based on Substituting Regional MRI Volume Scores.- Weakly supervised segmentation from extreme points.- Exploring the Relationship between Segmentation Uncertainty, Segmentation Performance and Inter-observer Variability with Probabilistic Networks.- DeepIGeoS-V2: Deep Interactive Segmentation of Multiple Organs from Head and Neck Images with Lightweight CNNs.- The Role of Publicly Available Data in MICCAI Papers from 2014 to 2018.- First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention (HAL-MICCAI 2019).- Hardware Acceleration of Persistent Homology Computation.- Deep Compressed Pneumonia Detection for Low-Power Embedded Devices.- D3MC: A Reinforcement Learning based Data-driven Dyna Model Compression.- An Analytical Method of Automatic Alignment for Electron Tomography.- Fixed-Point U-Net Quantization for Medical Image Segmentation.- Second International Workshop on Correction of Brainshift with Intra-Operative Ultrasound (CuRIOUS 2019).- Registration of ultrasound volumes based on Euclidean distance transform.- Landmark-based evaluation of a block-matching registration framework on the RESECT pre- and intra-operative brain image data set.- Comparing deep learning strategies and attention mechanisms of discrete registration for multimodal image-guided interventions.
Описание: Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep learning, including neural networks. The title helps researchers maximize the performance of Edge-deep learning models for mobile computing and other applications by presenting neural network algorithms and hardware design optimization approaches for Edge-deep learning. Applications are introduced in each section, and a comprehensive example, smart surveillance cameras, is presented at the end of the book, integrating innovation in both algorithm and hardware architecture. Structured into three parts, the book covers core concepts, theories and algorithms and architecture optimization. This book provides a solution for researchers looking to maximize the performance of deep learning models on Edge-computing devices through algorithm-hardware co-design.
Автор: Shi Jun Yi, Zhang Yu Xiao, Zhou de Qun Название: Illustrated Flora of Bambusoideae in China: Volume 1 ISBN: 9811578834 ISBN-13(EAN): 9789811578830 Издательство: Springer Цена: 76864.00 р. Наличие на складе: Нет в наличии.
Описание: This book is intended for periodontal residents and practicing periodontists who wish to incorporate the principles of moderate sedation into daily practice. Comprehensive airway management and rescue skills are then documented in detail so that the patient may be properly managed in the event that the sedation progresses beyond the intended level.
Автор: Shi Jun Yi, Zhang Yu Xiao, Zhou de Qun Название: Illustrated Flora of Bambusoideae in China: Volume 2 ISBN: 9811627576 ISBN-13(EAN): 9789811627576 Издательство: Springer Рейтинг: Цена: 53106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book was compiled by researchers of Chinese Academy of Forestry, Sichuan Agricultural University, Chinese Academy of Sciences, Southwest Forestry University, and Kunming University of Science and Technology.
Автор: Luping Zhou; Li Wang; Qian Wang; Yinghuan Shi Название: Machine Learning in Medical Imaging ISBN: 3319248871 ISBN-13(EAN): 9783319248875 Издательство: Springer Рейтинг: Цена: 7826.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 6th International Workshop on Machine Learning in Medical Imaging, MLMI 2015, held in conjunction with MICCAI 2015, in Munich in October 2015.
Описание: This book studies selected discrete-time flight control schemes for fixed-wing unmanned aerial vehicle (UAV) systems in the presence of system uncertainties, external disturbances and input saturation.
Автор: Shi Yusheng, Yan Chunze, Zhou Yan Название: Materials for Additive Manufacturing ISBN: 0128193026 ISBN-13(EAN): 9780128193020 Издательство: Elsevier Science Рейтинг: Цена: 38739.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Materials for Additive Manufacturing covers the materials utilized in the additive manufacturing field, including polymers, metals, alloys and ceramic materials. A conceptual overview of the preparation and characterization of the materials and their processing is given, beginning with theoretical aspects that help readers better understand fundamental concepts. Emerging applications in medicine, aerospace, automotive, artwork and rapid manufacturing are also discussed. This book provides a comprehensive overview of materials, along with rapid prototyping technologies.
Описание: This book develops an emergy accounting model and illustrates how emergy analysis can be used to compare different systems at different scales, ranging from urban areas to nationwide. It features a case study of China`s Macao special administrative region.
Автор: Zhou Shiyu Название: Industrial Data Analytics for Diagnosis and Prognosis ISBN: 1119666287 ISBN-13(EAN): 9781119666288 Издательство: Wiley Рейтинг: Цена: 17891.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Discover data analytics methodologies for the diagnosis and prognosis of industrial systems under a unified random effects model
In Industrial Data Analytics for Diagnosis and Prognosis - A Random Effects Modelling Approach, distinguished engineers Shiyu Zhou and Yong Chen deliver a rigorous and practical introduction to the random effects modeling approach for industrial system diagnosis and prognosis. In the book's two parts, general statistical concepts and useful theory are described and explained, as are industrial diagnosis and prognosis methods. The accomplished authors describe and model fixed effects, random effects, and variation in univariate and multivariate datasets and cover the application of the random effects approach to diagnosis of variation sources in industrial processes. They offer a detailed performance comparison of different diagnosis methods before moving on to the application of the random effects approach to failure prognosis in industrial processes and systems.
In addition to presenting the joint prognosis model, which integrates the survival regression model with the mixed effects regression model, the book also offers readers:
A thorough introduction to describing variation of industrial data, including univariate and multivariate random variables and probability distributions
Rigorous treatments of the diagnosis of variation sources using PCA pattern matching and the random effects model
An exploration of extended mixed effects model, including mixture prior and Kalman filtering approach, for real time prognosis
A detailed presentation of Gaussian process model as a flexible approach for the prediction of temporal degradation signals
Ideal for senior year undergraduate students and postgraduate students in industrial, manufacturing, mechanical, and electrical engineering, Industrial Data Analytics for Diagnosis and Prognosis is also an indispensable guide for researchers and engineers interested in data analytics methods for system diagnosis and prognosis.
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