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: Computer vision and recognition systems
    sub title: research innovations and trends
  name:
    name part: Chowdhary, Chiranji Lal
    name part: 1975-
    role:
      role term: editor.
  name:
    name part: Reddy, G. Thippa
    role:
      role term: editor.
  name:
    name part: Parameshachari, B. D.
    name part: 1981-
    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 : illustrations
  abstract: "This cutting-edge volume, Computer Vision and Recognition Systems: Research Innovations and Trends, focuses on how artificial intelligence can be used to give computers the ability to imitate human sight. It explains the essential modules that are necessary for comprehending artificial intelligence experiences to provide machines with the power of vision. With contributions from researchers in diverse countries, including Thailand, Spain, Japan, Turkey, Australia, and India, the book discusses how machine learning and deep learning are important aspects in computer vision and recognition systems. The volume also presents a number of innovative research developments, applications, and current trends in the field. The chapters cover such topics as visual quality improvement, Parkinson's disease diagnosis, hypertensive retinopathy detection through retinal fundus, big image data processing, N-grams for image classification, medical brain images, chatbot applications, credit score improvisation, vision-based lane and vehicle detection, damaged vehicle parts recognition, partial image encryption of medical images, and image synthesis. The chapter authors show different approaches to computer vision, image processing, and frameworks for machine learning to build automated and stable applications. Deep learning is included for making immersive application-based systems, pattern recognition, and biometric systems. The book also considers efficiency and comparison at various levels of using algorithms for real-time applications, processes, and analysis. This volume provides a rich source of information for researchers, professionals, and anyone working in computer vision and recognition systems." --
  table of contents: Visual Quality Improvement Using Single Image Defogging Technique / Pritam Verma and Vijay Kumar -- A Comparative Study of Machine Learning Algorithms in Parkinson's Disease Diagnosis: A Review / Pedram Khatamino and Zeynep Orman -- Machine Learning Algorithms for Hypertensive Retinopathy Detection through Retinal Fundus Images / N. Jagan Mohan, R. Murugan, and Tripti Goel -- Big Image Data Processing: Methods, Technologies, and Implementation Issues / U. S. N. Raju, Suresh Kumar Kanaparthi, Mahesh Kumar Morampudi, Sweta Panigrahi, and Debanjan Pathak -- N-grams for Image Classification and Retrieval / Pradnya S. Kulkarni -- A Survey on Evolutionary Algorithms for Medical Brain Images / Nurşah Dincer and Zeynep Orman -- Chatbot Application with Scene Graph in Thai Language / Chantana Chantrapornchai and Panida Khuphira -- Credit Score Improvisation through Automating the Extraction of Sentiment from Reviews / Aadit Vikas Malikayil, Maheswari R., Azath H., and Sharmila P. -- Vision-Based Lane and Vehicle Detection: A First Step Toward Autonomous Unmanned Vehicle / Tapan Kumar Das -- Damaged Vehicle Parts Recognition Using Capsule Neural Network / Kundjanasith Thonglek, Norawit Urailertprasert, Patchara Pattiyathanee, and Chantana Chantrapornchai -- Partial Image Encryption of Medical Images Based on Various Permutation Techniques / Kiran, B. D. Parameshachari, H. T. Panduranga, and Rocío Pérez de Prado -- Image Synthesis with Generative Adversarial Networks (GAN) / Parvathi R. and Pattabiraman V.
  note: edited by Chiranji Lal Chowdhary, PhD, G. Thippa Reddy, PhD, B. D. Parameshachari, PhD.
  note: Includes bibliographical references and index.
  subject:
    topic: Computer vision
  subject:
    topic: Artificial intelligence
  subject:
    topic: Pattern recognition systems
  subject:
    topic: Vision par ordinateur
  subject:
    topic: Intelligence artificielle
  subject:
    topic: Reconnaissance des formes (Informatique)
  subject:
    topic: artificial intelligence
  subject:
    topic: SCIENCE / General
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computer vision
  subject:
    topic: Pattern recognition systems
  classification: TA1634 .C66 2022
  classification: 006.3/7
  classification: cci1iic
  classification: cci1icc
  related item:
    title info:
      title: Computer vision and recognition systems
    origin info:
      publisher: Palm Bay, FL, USA ; Burlington, ON, Canada : Apple Academic Press ; Boca Raton, FL, USA ; Abingdon, Oxon, UK : CRC Press, 2022
      edition: First edition.
    identifier: (DLC) 2021045079
    identifier: (OCoLC)1232272873
  identifier: 9781003180593
  identifier: 1003180590
  identifier: 9781000400779
  identifier: 1000400778
  identifier: 9781000401028
  identifier: 1000401022
  identifier: 9781774630150
  identifier: 177463015X
  identifier: 9781774639368
  identifier: 177463936X
  identifier: 9781003180593 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: NLC
    record creation date: 210910
    record change date: 20241108165659.9
    record identifier: in00005522477
    language of cataloging:
      language term: eng