rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Advances in deep learning for medical image analysis
  name:
    name part: Mire, Archana
    role:
      role term: editor.
  name:
    name part: Elangovan, Vinayak
    role:
      role term: editor.
  name:
    name part: Patil, Shailaja
    role:
      role term: editor.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2022
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: "This reference text introduces the classical probabilistic model, deep learning, and big data techniques for improving medical imaging and detecting various diseases. The text addresses a wide variety of application areas in medical imaging where deep learning techniques provide solutions with lesser human intervention and reduced time. It comprehensively covers important machine learning for signal analysis, deep learning techniques for cancer detection, diabetic cases, skin image analysis, Alzheimer's disease detection, coronary disease detection, medical image forensic, fetal anomaly detection, and plant phytology. The text will serve as a useful text for graduate students and academic researchers in the fields of electronics engineering, computer science, biomedical engineering, and electrical engineering"--
  note: edited by Archana Mire, Vinayak Elangovan and Shailaja Patil.
  note: Includes bibliographical references and index.
  note: Archana Mire is presently working as Head, Department of computer engineering, Terna Engineering College, Navi Mumbai, India. She has more than 14 years of research and teaching experience. She has published research papers in various SCI/Scopus indexed national/international conferences and journals. She has worked on various national/International conference technical committees and reviewed papers for various conferences and journals. She has served as a session chair for various international conferences organized within and outside India. Her main research area is machine learning and image processing. Vinayak Elangovan is currently working as an assistant professor of Computer Science at Penn State University in Abington, USA. He earned his Ph.D. in Computer Information Systems Engineering at Tennessee State University, the USA in 2014, and continued his research and teaching there as a Postdoctoral fellow. He worked at The College of New Jersey (TCNJ) and St. Olaf College teaching various computer science courses for undergraduate students during 2015-2017. His research interest includes computer vision, machine vision, multi-sensor data fusion, and activity sequence analysis with a keen interest in software applications development and database management. He has worked on a number of funded projects related to the Department of Defense and the Department of Homeland Security applications. He also has considerable work experience in the engineering and software industries. Shailaja Patil is currently working as a professor, department of electronics and telecommunication, and Dean (Research and Development), Rajarshi Shahu College of Engineering, Pune, India. She has 25 years of teaching and 3 years of research experience. She has more than 60 publications in peer-reviewed journals. She has delivered expert lectures on WSN, SDN, and Intellectual property Rights at various workshops. She is a Fellow of the Institution of Engineers and members of various profe…
  subject:
    topic: Diagnostic imaging
  subject:
    topic: Image analysis
  subject:
    topic: Diagnostic Imaging
  subject:
    topic: Imagerie pour le diagnostic
  subject:
    topic: Analyse d'images
  subject:
    topic: TECHNOLOGY / Imaging Systems
  subject:
    topic: TECHNOLOGY / Electronics / General
  subject:
    topic: Diagnostic imaging
  subject:
    topic: Image analysis
  classification: RC78.7.D53
  classification: 616.07/54
  related item:
    title info:
      title: Advances in deep learning for medical image analysis
    origin info:
      publisher: Boca Raton : CRC Press, 2022
      edition: First edition.
    identifier: (DLC) 2021053527
  identifier: 9781000575996
  identifier: 1000575993
  identifier: 9781003230540
  identifier: 1003230547
  identifier: 9781000575958
  identifier: 1000575950
  identifier: 9781032137162
  identifier: 9781032137193
  identifier: 2021053528
  identifier: 9781003230540 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: DLC
    record creation date: 211208
    record change date: 20241108170103.2
    record identifier: in00005526551
    language of cataloging:
      language term: eng