標(biāo)題: Titlebook: Bridging the Semantic Gap in Image and Video Analysis; Halina Kwa?nicka,Lakhmi C. Jain Book 2018 Springer International Publishing AG 2018 [打印本頁] 作者: DEBUT 時間: 2025-3-21 16:59
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書目名稱Bridging the Semantic Gap in Image and Video Analysis被引頻次
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書目名稱Bridging the Semantic Gap in Image and Video Analysis讀者反饋
書目名稱Bridging the Semantic Gap in Image and Video Analysis讀者反饋學(xué)科排名
作者: VAN 時間: 2025-3-21 22:14 作者: 結(jié)構(gòu) 時間: 2025-3-22 02:13 作者: modish 時間: 2025-3-22 06:35 作者: Ointment 時間: 2025-3-22 11:02 作者: TATE 時間: 2025-3-22 15:11 作者: 保存 時間: 2025-3-22 19:42
Bridging the Semantic Gap in Image and Video Analysis978-3-319-73891-8Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: 閑逛 時間: 2025-3-22 21:45
Siavash H. Khajavi,Mika Salmi,Jan Holmstr?mage, 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作者: follicular-unit 時間: 2025-3-23 03:49
https://doi.org/10.1007/978-0-306-48567-1accurately as possible, areas with a certain level of semantic uniformity on top of the default pictorial uniformity of regions extracted by the segmentation methods. Obviously, the results should be insensitive to noise, textures, and other effects typically distorting such uniformities. This chapt作者: 貨物 時間: 2025-3-23 08:52 作者: Lipoma 時間: 2025-3-23 13:13 作者: BANAL 時間: 2025-3-23 14:16 作者: 浮雕 時間: 2025-3-23 21:45
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作者: inveigh 時間: 2025-3-23 23:37
Halina Kwa?nicka,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作者: 行業(yè) 時間: 2025-3-24 06:05
Intelligent Systems Reference Libraryhttp://image.papertrans.cn/b/image/190787.jpg作者: prostatitis 時間: 2025-3-24 07:20 作者: Grating 時間: 2025-3-24 12:21
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.作者: 急急忙忙 時間: 2025-3-24 18:49 作者: Altitude 時間: 2025-3-24 22:07 作者: OGLE 時間: 2025-3-25 02:54
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作者: 百靈鳥 時間: 2025-3-25 04:04
,Scale-Insensitive MSER Features: A?Promising Tool for Meaningful Segmentation of Images,accurately as possible, areas with a certain level of semantic uniformity on top of the default pictorial uniformity of regions extracted by the segmentation methods. Obviously, the results should be insensitive to noise, textures, and other effects typically distorting such uniformities. This chapt作者: 墻壁 時間: 2025-3-25 10:44 作者: Graphite 時間: 2025-3-25 11:57 作者: expire 時間: 2025-3-25 18:40 作者: 匍匐前進(jìn) 時間: 2025-3-25 20:12 作者: 吹牛需要藝術(shù) 時間: 2025-3-26 00:09
Bridging the Semantic Gap in Image and Video Analysis作者: leniency 時間: 2025-3-26 07:06 作者: 樹膠 時間: 2025-3-26 11:36
1868-4394 rs, students and professors in Computer Engineering, Computer Science and related fields whose work involves images, video analysis, image interpretation and so on..978-3-030-08879-8978-3-319-73891-8Series ISSN 1868-4394 Series E-ISSN 1868-4408 作者: 骯臟 時間: 2025-3-26 13:28 作者: Indolent 時間: 2025-3-26 17:38
https://doi.org/10.1007/978-0-306-48567-1st mobile devices. First, the chapter presents fundamentals of SIMSER detector (and the original MSER detector) in gray-level images. Then, relations between semantics-based image annotation and SIMSER features are investigated and illustrated by extensive experiments (including color images, which 作者: 疲勞 時間: 2025-3-26 21:29
Tools and Resources for Your Speakers,titions not an optimal contour is sought but optimal partition of given element set is looked for. The change of image content description is advantageous as well. It reduces the size of search space and allows humans to express their knowledge in more intuitive way.作者: affinity 時間: 2025-3-27 01:53
Ethics, Regulations, and Explainability,s presented in more details. Testing scenarios deal with the recognition of cups and bottles or household furniture. Conducted experiments and the chosen applications confirmed, that this approach is valid and may easily be adapted to multiple scenarios.作者: Heart-Attack 時間: 2025-3-27 05:23
Low-Level Feature Detectors and Descriptors for Smart Image and Video Analysis: A Comparative Studyapter is to provide a comparative study of the most used and popular low-level local feature extractors: SIFT, SURF, ORB, PHOG, WGCH, Haralick and A-KAZE. At first, the chapter starts by providing an overview of the different extractors referenced in a concrete case study to show their potentiality 作者: KEGEL 時間: 2025-3-27 11:08
,Scale-Insensitive MSER Features: A?Promising Tool for Meaningful Segmentation of Images,st mobile devices. First, the chapter presents fundamentals of SIMSER detector (and the original MSER detector) in gray-level images. Then, relations between semantics-based image annotation and SIMSER features are investigated and illustrated by extensive experiments (including color images, which 作者: MAIZE 時間: 2025-3-27 17:35 作者: 警告 時間: 2025-3-27 21:29
Model-Based 3D Object Recognition in RGB-D Images,s presented in more details. Testing scenarios deal with the recognition of cups and bottles or household furniture. Conducted experiments and the chosen applications confirmed, that this approach is valid and may easily be adapted to multiple scenarios.作者: bizarre 時間: 2025-3-27 22:09
Kathleen Renked a laboratory manual that is both easy to use in the laboratory and which will be updated as the techniques change and new technologies are devised. Additional chapters that can replace or be added to this first edition will be published periodically. The editors recognize that many of the techniq作者: HPA533 時間: 2025-3-28 04:16
Book 2016ro link; and, (3) Theorizing the social world rather than celebrating theorists or theories; that is, one can look at how theory is used holistically to understand the constraints the social world places on our lived experience or the dynamics of social change. Hence, in the second decade of the 21s作者: Endoscope 時間: 2025-3-28 08:30
https://doi.org/10.1007/BFb0100174difference equation; eXist; equation; online; proof作者: 全等 時間: 2025-3-28 13:44 作者: 泰然自若 時間: 2025-3-28 16:36
