This book provides the first systematic study of facial kinship verification, a new research topic in biometrics. It presents three key aspects of facial kinship verification: 1) feature learning for kinship verification, 2) metric learning for kinship verification, and 3) video-based kinship verification, and reviews state-of-the-art research findings on facial kinship verification. Many of the feature-learning and metric-learning methods presented in this book can also be easily applied for other face analysis tasks, e.g., face recognition, facial expression recognition, facial age estimation and gender classification. Further, it is a valuable resource for researchers working on other computer vision and pattern recognition topics such as feature-learning-based and metric-learning-based visual analysis.
Entrepreneurship is hot. China is hot. Combining these two concepts could therefore be a dangerous act, as it may cause overheating. Chinese entrepreneurs are indeed the subject of a rapidly growing body of literature, academic and popular. However, the bulk of it tends to focus on a few aspects. There are the biographies of ‘famous’ entrepreneurs. While informative, these are usually of a non-academic nature. Academic studies tend to focus on the political and economic environment in which present day Chinese entrepreneurs have to operate. Both types of publications slight the entrepreneurial identity. This study aims at filling this gap with its core question: why do some people become entrepreneurs? The authors have analysed the life stories of a number of Chinese private entrepreneurs to reveal how the entrepreneurial identity of each of them has emerged at the cross section of an number of other identities. This book therefore contributes to a better understanding of Chinese entrepreneurship and the study of entrepreneurship in general.
This book provides the first systematic study of facial kinship verification, a new research topic in biometrics. It presents three key aspects of facial kinship verification: 1) feature learning for kinship verification, 2) metric learning for kinship verification, and 3) video-based kinship verification, and reviews state-of-the-art research findings on facial kinship verification. Many of the feature-learning and metric-learning methods presented in this book can also be easily applied for other face analysis tasks, e.g., face recognition, facial expression recognition, facial age estimation and gender classification. Further, it is a valuable resource for researchers working on other computer vision and pattern recognition topics such as feature-learning-based and metric-learning-based visual analysis.
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