Computer Vision: Object Detection In Adversarial Vision
暫譯: 計算機視覺：對抗性視覺中的物體檢測
Bhowmik, Mrinal Kanti
- 出版商: CRC
- 出版日期: 2025-12-26
- 售價: $2,870
- 貴賓價: 9.5 折 $2,727
- 語言: 英文
- 頁數: 190
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1032557494
- ISBN-13: 9781032557496
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相關分類:
Computer Vision
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相關主題
商品描述
This comprehensive textbook presents a broad review of both traditional (i.e., conventional) and deep learning aspects of object detection in various adversarial real-world conditions in a clear, insightful, and highly comprehensive style. Beginning with the relation of computer vision and object detection, the text covers the various representation of
objects, applications of object detection, and real-world challenges faced by the research community for object detection task. The book addresses various real-world degradations and artifacts for the object detection task and also highlights the impacts of artifacts in the object detection problems. The book covers various imaging modalities and benchmark datasets mostly adopted by the research community for solving various aspects of object detection tasks. The book also collects together solutions and perspectives proposed by the preeminent researchers in the field, addressing not only the background of visibility enhancement but also techniques proposed in the literature for visibility enhancement of scenes and detection of objects in various representative real-world challenges.
Computer Vision: Object Detection in Adversarial Vision is unique for its diverse content, clear presentation, and overall completeness. It provides a clear, practical, and detailed introduction and advancement of object detection in various representative challenging real-world conditions.
Topics and Features:
- Offers the first truly comprehensive presentation of aspects of the object detection in degraded and nondegraded environment.
- Includes in-depth discussion of various degradation and artifacts, and impact of those artifacts in the real world on solving the object detection problems.
- Gives detailed visual examples of applications of object detection in the real world.
- Presents a detailed description of popular imaging modalities for object detection adopted by researchers.
- Presents the key characteristics of various benchmark datasets in indoor and outdoor environment for solving object detection tasks.
- Surveys the complete field of visibility enhancement of degraded scenes, including conventional methods designed for enhancing the degraded scenes as well as the deep architectures.
- Discusses techniques for detection of objects in real-world applications.
- Contains various hands-on practical examples and a tutorial for solving object detection problems using Python.
- Motivates readers to build vision-based systems for solving object detection problems in degraded and nondegraded real-world challenges.
The book will be of great interest to a broad audience ranging from researchers and practitioners to graduate and postgraduate students involved in computer vision tasks with respect to object detection in degraded and nondegraded real-world vision problems.
商品描述(中文翻譯)
這本綜合性的教科書以清晰、深刻且全面的風格，廣泛回顧了在各種對抗性現實條件下物體檢測的傳統（即常規）和深度學習方面。書中首先探討了計算機視覺與物體檢測的關係，接著涵蓋了物體的各種表徵、物體檢測的應用，以及研究社群在物體檢測任務中面臨的現實挑戰。該書針對物體檢測任務中的各種現實退化和伪影進行了探討，並強調了伪影對物體檢測問題的影響。書中涵蓋了研究社群主要採用的各種影像模式和基準數據集，以解決物體檢測任務的各個方面。此外，該書還匯集了該領域內卓越研究者提出的解決方案和觀點，不僅涉及可見性增強的背景，還包括文獻中提出的場景可見性增強技術及在各種代表性現實挑戰中檢測物體的技術。
《計算機視覺：對抗視覺中的物體檢測》因其多樣的內容、清晰的呈現和整體的完整性而獨樹一幟。它提供了在各種具有挑戰性的現實條件下，物體檢測的清晰、實用和詳細的介紹與進展。
主題與特點：
- 提供了對退化和非退化環境中物體檢測各方面的首次真正全面的呈現。
- 包含對各種退化和伪影的深入討論，以及這些伪影在現實世界中對解決物體檢測問題的影響。
- 提供了物體檢測在現實世界應用的詳細視覺範例。
- 詳細描述了研究人員採用的流行影像模式以進行物體檢測。
- 呈現了解決物體檢測任務所需的室內和室外環境中各種基準數據集的關鍵特徵。
- 調查了退化場景的可見性增強的完整領域，包括旨在增強退化場景的傳統方法以及深度架構。
- 討論了在現實應用中檢測物體的技術。
- 包含各種實用的實作範例和使用 Python 解決物體檢測問題的教程。
- 激勵讀者建立基於視覺的系統，以解決退化和非退化現實挑戰中的物體檢測問題。
這本書將對廣泛的讀者群體產生極大興趣，從研究人員和實務工作者到參與計算機視覺任務的研究生和研究所學生，特別是在退化和非退化的現實視覺問題中的物體檢測。
作者簡介
Mrinal Kanti Bhowmik earned a Bachelor of Engineering (BE) degree in Computer Science and Engineering from the Tripura Engineering College, Government of Tripura, in 2004, a Master of Technology (M.Tech) degree in Computer Science and Engineering from Tripura University (A Central University), India, in 2007, and a PhD in Engineering from Jadavpur University, Kolkata, India, in 2014. He has also spent the Fall 2022 session as a DST-SERB International Research Experience (SIRE) Scholar with SIRE Fellowship, sponsored by the Science and Engineering Research Board (SERB), Government of India at the NYU Center for Cybersecurity (CCS), Tandon School of Engineering, New York University, New York City. He has successfully completed two Department of Electronics and Information Technology (DeitY) (Now Ministry of Electronics and Information Technology [MeitY])-funded projects, one Department of Biotechnology (DBT)-Twinning project, one Society for Applied Microwave Electronics Engineering and Research (SAMEER)-funded project, one Indian Council of Medical Research (ICMR) project, and one Defence Research and Development Organisation (DRDO) project as the Principal Investigator. He is currently the Principal Investigator of one Department of Biotechnology (DBT)-funded project and Co-Principal Investigator of one Indian Council of Medical Research (ICMR) project in collaboration with All India Institute of Medical Sciences (AIIMS), New Delhi.
Since July 2010, he has served with the Department of Computer Science and Engineering, Tripura University as an Assistant Professor and from 26th March, 2023 he has been serving with Department of Computer Science and Engineering, Tripura University as an Associate Professor. He was awarded the Short Term Indian Council of Medical Research (ICMR), Department of Health Research (DHR) International Fellowship from 2019 to 2020 as a Senior Indian Biomedical Scientist for bilateral cooperation in cross-disciplinary research area (i.e., biomedical diagnostic and inferencing systems). His research team has also designed two datasets for object detection in degraded vision named Extended Tripura University Video Dataset (E-TUVD) and Tripura University Video Dataset at Night time (TU-VDN) dataset for the research community in the proposed domain of object detection. His current research interests are in the fields of computer vision, security and surveillance, medical imaging, and image and video forensics.
作者簡介(中文翻譯)
Mrinal Kanti Bhowmik 於2004年獲得印度特里普拉工程學院（Tripura Engineering College, Government of Tripura）計算機科學與工程（Computer Science and Engineering）學士學位（BE），於2007年獲得特里普拉大學（Tripura University，中央大學）計算機科學與工程碩士學位（M.Tech），並於2014年獲得印度加爾各答的賈達夫普爾大學（Jadavpur University）工程博士學位（PhD）。他於2022年秋季擔任印度政府科學與工程研究委員會（Science and Engineering Research Board, SERB）贊助的DST-SERB國際研究經驗（SIRE）獎學金獲得者，並在紐約大學坦登工程學院（Tandon School of Engineering, New York University）網絡安全中心（Center for Cybersecurity, CCS）進行研究。他成功完成了兩個由電子與信息技術部（Department of Electronics and Information Technology, DeitY，現為電子與信息技術部 [MeitY]）資助的項目、一個生物技術部（Department of Biotechnology, DBT）雙聯項目、一個應用微波電子工程與研究協會（Society for Applied Microwave Electronics Engineering and Research, SAMEER）資助的項目、一個印度醫學研究委員會（Indian Council of Medical Research, ICMR）項目，以及一個國防研究與發展組織（Defence Research and Development Organisation, DRDO）項目，並擔任主要研究者。目前，他是由生物技術部（DBT）資助的一個項目的主要研究者，以及與新德里的全印度醫學科學院（All India Institute of Medical Sciences, AIIMS）合作的一個印度醫學研究委員會（ICMR）項目的共同主要研究者。
自2010年7月以來，他在特里普拉大學計算機科學與工程系擔任助理教授，並自2023年3月26日起擔任副教授。他於2019年至2020年獲得印度醫學研究委員會（ICMR）健康研究部（Department of Health Research, DHR）短期國際獎學金，作為高級印度生物醫學科學家，促進跨學科研究領域（即生物醫學診斷與推理系統）的雙邊合作。他的研究團隊還為退化視覺中的物體檢測設計了兩個數據集，分別為擴展特里普拉大學視頻數據集（Extended Tripura University Video Dataset, E-TUVD）和特里普拉大學夜間視頻數據集（Tripura University Video Dataset at Night time, TU-VDN），以供物體檢測領域的研究社群使用。他目前的研究興趣包括計算機視覺、安全與監控、醫學影像以及影像與視頻取證。
