Bridging the Semantic Gap in Image and Video Analysis
暫譯: 縮小影像與影片分析中的語意差距
Kwaśnicka, Halina, Jain, Lakhmi C.
- 出版商: Springer
- 出版日期: 2019-01-24
- 售價: $2,470
- 貴賓價: 9.5 折 $2,347
- 語言: 英文
- 頁數: 163
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3030088790
- ISBN-13: 9783030088798
海外代購書籍(需單獨結帳)
商品描述
This book presents cutting-edge research on various ways to bridge the semantic gap in image and video analysis. The respective chapters address different stages of image processing, revealing that the first step is a future extraction, the second is a segmentation process, the third is object recognition, and the fourth and last involve the semantic interpretation of the image.
The semantic gap is a challenging area of research, and describes the difference between low-level features extracted from the image and the high-level semantic meanings that people can derive from the image. The result greatly depends on lower level vision techniques, such as feature selection, segmentation, object recognition, and so on. The use of deep models has freed humans from manually selecting and extracting the set of features. Deep learning does this automatically, developing more abstract features at the successive levels.
The book offers a valuable resource for researchers, practitioners, students and professors in Computer Engineering, Computer Science and related fields whose work involves images, video analysis, image interpretation and so on.
商品描述(中文翻譯)
本書介紹了關於縮小影像和視頻分析中語意差距的各種前沿研究。各章節針對影像處理的不同階段進行探討，顯示第一步是特徵提取，第二步是分割過程，第三步是物體識別，第四步也是最後一步則涉及影像的語意解釋。
語意差距是一個具有挑戰性的研究領域，描述了從影像中提取的低階特徵與人們能從影像中推導出的高階語意之間的差異。結果在很大程度上依賴於低階視覺技術，例如特徵選擇、分割、物體識別等。深度模型的使用使人類不再需要手動選擇和提取特徵集。深度學習自動完成這一過程，在各個層次上發展出更抽象的特徵。
本書為計算機工程、計算機科學及相關領域的研究人員、實務工作者、學生和教授提供了寶貴的資源，這些人的工作涉及影像、視頻分析、影像解釋等。
作者簡介
Professor Dr Halina Kwaśnicka is a Head of Department of Computational Intelligence at Wroclaw University of Science and Technology, Wroclaw, Poland and the Director of Graduate Schools. She was the Deputy Director for Scientific Researches of Institute of Informatics and the head of Division of Artificial Intelligence (in the Institute of Informatics).
Over time, her research interest has evolved from nature-inspired methods, data mining, and knowledge-based systems to methods of generation of hierarchies of groups of objects, in the further goal to use them in clustering text documents and images. Such a hierarchy of images projected on ontology could allow inferring semantic content.\
Professor Kwaśnicka was and is involved in the realization of scientific national and international projects, and published as an author or co-author more than 200 journal and conference papers and books.
Dr. Lakhmi C. Jain, PhD, ME, BE(Hons), Fellow (Engineers Australia) is with the Faculty of Education, Science, Technology & Mathematics at the University of Canberra, Australia and Bournemouth University, UK.
Professor Jain founded the KES International for providing a professional community the opportunities for publications, knowledge exchange, cooperation and teaming. Involving around 5,000 researchers drawn from universities and companies world-wide, KES facilitates international cooperation and generate synergy in teaching and research. KES regularly provides networking opportunities for professional community through one of the largest conferences of its kind in the area of KES.
His interests focus on the artificial intelligence paradigms and their applications in complex systems, security, e-education, e-healthcare, unmanned air vehicles and intelligent agents.作者簡介(中文翻譯)
教授哈莉娜·克瓦斯尼卡（Halina Kwaśnicka）是波蘭弗羅茨瓦夫科技大學（Wroclaw University of Science and Technology）計算智慧系所的系主任及研究所的研究生院院長。她曾擔任資訊學研究所的科學研究副所長及人工智慧部門的負責人。
隨著時間的推移，她的研究興趣從自然啟發的方法、資料探勘和知識基礎系統，演變為生成物件群組層級的方法，進一步的目標是將其應用於文本文件和圖像的聚類。這樣的圖像層級投影於本體論上，可能允許推斷語義內容。
克瓦斯尼卡教授曾參與國內外科學專案的實施，並以作者或合著者身份發表了超過200篇期刊和會議論文及書籍。
拉克米·C·賈因博士（Dr. Lakhmi C. Jain），博士、碩士、榮譽學士，澳大利亞工程師協會（Engineers Australia）院士，現任澳大利亞坎培拉大學（University of Canberra）及英國伯恩茅斯大學（Bournemouth University）教育、科學、技術與數學學院的教職。
賈因教授創立了KES國際組織，為專業社群提供發表、知識交流、合作和團隊合作的機會。KES吸引了來自全球大約5,000名研究人員，促進國際合作並在教學和研究中產生協同效應。KES定期透過其領域內最大的會議之一，為專業社群提供網絡交流的機會。
他的研究興趣集中於人工智慧範式及其在複雜系統、安全性、電子教育、電子醫療、無人飛行器和智能代理中的應用。
