Titlebook: Bridging the Semantic Gap in Image and Video Analysis; Halina Kwaśnicka,Lakhmi C. Jain Book 2018 Springer International Publishing AG 2018

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https://doi.org/10.1007/978-1-908517-14-2problem of how to overcome the semantic gap remains a challenge. One of the most popular research areas, where this problem is present and causes difficulty in obtaining good results, is the task of image retrieval. This chapter focuses on this problem. As deep learning models gain more and more pop

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Halina Kwaśnicka,Lakhmi C. JainPresents cutting-edge research on various ways to bridge the semantic gap in image and video analysis.Explores the correspondence between the low-level information extracted from an image and the mean

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Semantic Gap in Image and Video Analysis: An Introduction,The chapter presents a brief introduction to the problem with the semantic gap in content-based image retrieval systems. It presents the complex process of image processing, leading from raw images, through subsequent stages to the semantic interpretation of the image. Next, the content of all chapters included in this book is shortly presented.

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Low-Level Feature Detectors and Descriptors for Smart Image and Video Analysis: A Comparative Studyage, a set of discriminative patterns (hereinafter keypoints) present on some parts of background and/or foreground elements of the image itself. A prerequisite of a wide range of practical applications (e.g., vehicle tracking, person re-identification) is the design and development of algorithms ab