The Tao Illuminated Contextual Annotations For Deeper Understanding
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The Tao Illuminated: Contextual Annotations for Deeper Understanding
Unveiling the Profound Wisdom of the Tao Te Ching This meticulously crafted book offers a comprehensive and illuminating guide to the enigmatic Tao Te Ching. With in-depth contextual annotations, readers will delve into the timeless teachings of this ancient classic, gaining a deeper understanding of its profound insights into life, nature, and the cosmos. Tailored for both seasoned seekers and newcomers alike, this book unravels the enigmatic verses of the Tao Te Ching, providing a lucid framework for comprehending their essential meaning. Its annotations elucidate the cultural, historical, and philosophical context of each passage, allowing readers to grasp the nuances and connections that enrich the text. Embark on an intellectual odyssey that explores the core concepts of the Tao, such as wu-wei (non-action), yin and yang, and the transformative power of embracing the natural order. Through its detailed analysis and engaging prose, this book invites readers to not only comprehend the words of the Tao Te Ching but to embody its wisdom in their own lives. Why Choose This Book? - Gain a comprehensive understanding of the Tao Te Ching with in-depth annotations. - Explore the cultural, historical, and philosophical context of each verse.
Deep Learning for Hyperspectral Image Analysis and Classification
This book focuses on deep learning-based methods for hyperspectral image (HSI) analysis. Unsupervised spectral-spatial adaptive band-noise factor-based formulation is devised for HSI noise detection and band categorization. The method to characterize the bands along with the noise estimation of HSIs will benefit subsequent remote sensing techniques significantly. This book develops on two fronts: On the one hand, it is aimed at domain professionals who want to have an updated overview of how hyperspectral acquisition techniques can combine with deep learning architectures to solve specific tasks in different application fields. On the other hand, the authors want to target the machine learning and computer vision experts by giving them a picture of how deep learning technologies are applied to hyperspectral data from a multidisciplinary perspective. The presence of these two viewpoints and the inclusion of application fields of remote sensing by deep learning are the original contributions of this review, which also highlights some potentialities and critical issues related to the observed development trends.
Semantic Mining Technologies for Multimedia Databases
Provides an introduction to recent techniques in multimedia semantic mining necessary to researchers new to the field.