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: Machine Intelligence and Emerging Technologies
    sub title: First International Conference, MIET 2022, Noakhali, Bangladesh, September 23-25, 2022, Proceedings, Part I
  name:
    name part: Satu, Md. Shahriare.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Moni, Mohammad Ali.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Kaiser, M. Shamim.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Arefin, Mohammad Shamsul.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: sz
    date issued: 2023
    edition: 1st ed. 2023.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XXXI, 571 pages 362 illustrations, 201 illustrations in color.)
  abstract: The two-volume set LNICST 490 and 491 constitutes the proceedings of the First International Conference on Machine Intelligence and Emerging Technologies, MIET 2022, hosted by Noakhali Science and Technology University, Noakhali, Bangladesh, during September 23-25, 2022. The 104 papers presented in the proceedings were carefully reviewed and selected from 272 submissions. This book focuses on theoretical, practical, state-of-art applications, and research challenges in the field of artificial intelligence and emerging technologies. It will be helpful for active researchers and practitioners in this field. These papers are organized in the following topical sections: imaging for disease detection; pattern recognition and natural language processing; bio signals and recommendation systems for wellbeing; network, security and nanotechnology; and emerging technologies for society and industry.
  table of contents: Imaging for Disease Detection: Potato-Net: Classifying Potato Leaf Diseases Using Transfer Learning Approach -- False Smut Disease Detection in Paddy using Convolutional Neural Network -- Gabor Wavelet based Fused Texture Features for Identification of Mungbean Leaf Diseases -- Potato Disease Detection Using Convolutional Neural Network: A Web Based Solution -- Device-friendly Guava fruit and leaf disease detection using deep learning -- Cassava Leaf Disease Classification using Supervised Contrastive Learning -- Diabetes Mellitus prediction using Transfer Learning -- An Improved Heart Disease Prediction Using Stacked Ensemble Method -- Improved and Intelligent Heart Disease Prediction System Using Machine Learning Algorithm -- PreCKD_ML: Machine Learning Based Development of Prediction Model for Chronic Kidney Disease and Identify Significant Risk Factors -- A Reliable and Efficient Transfer Learning Approach for Identifying COVID-19 Pneumonia from Chest X-ray -- Infection Segmentation from COVID-19 Chest CT Scans with Dilated CBAM U-Net -- Convolutional Neural Network Model to Detect COVID-19 Patients Utilizing Chest X-ray Images -- Classification of Tumor Cell Using a Naive Convolutional Neural Network Model -- Tumor-TL: A Transfer Learning Approach for Classifying Brain Tumors from MRI Images -- Deep Convolutional Comparison Architecture for Breast Cancer Binary Classification -- Lung Cancer Detection from Histopathological Images using Deep Learning -- Brain Tumor Detection Using Deep Network EfficientNet-B0 -- Cancer Diseases Diagnosis Using Deep Transfer Learning Architectures -- Transfer Learning Based Skin Cancer Classification using GoogLeNet -- Assessing the Risks of COVID-19 on the Health Conditions of Alzheimer's Patients Using Machine Learning Techniques -- MRI based automated detection of Brain Tumor using DWT, GLCM, PCA, ensemble of SVM and PNN in sequence -- Pattern Recognition and Natural Language Processing: Performance Analysis of ASUS Tinker and…
  note: edited by Md. Shahriare Satu, Mohammad Ali Moni, M. Shamim Kaiser, Mohammad Shamsul Arefin.
  subject:
    topic: Computer networks
  subject:
    topic: Computer systems
  subject:
    topic: Software engineering
  subject:
    topic: Computer programming
  subject:
    topic: Computer Communication Networks
  subject:
    topic: Computer System Implementation
  subject:
    topic: Software Engineering
  subject:
    topic: Programming Techniques
  classification: TK5105.5-5105.9
  classification: 004.6
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 490
  identifier: 9783031346194
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 230610
    record change date: 20240805185630.3
    record identifier: in00004740244