Proceedings of the International Con...
International Conference on Big Data, IoT, and Machine Learning ((2021 :)

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  • Proceedings of the International Conference on Big Data, IoT, and Machine Learning = BIM 2021 /
  • Record Type: Electronic resources : Monograph/item
    Title/Author: Proceedings of the International Conference on Big Data, IoT, and Machine Learning/ edited by Mohammad Shamsul Arefin ... [et al.].
    Reminder of title: BIM 2021 /
    remainder title: BIM 2021
    other author: Arefin, Mohammad Shamsul.
    corporate name: International Conference on Big Data, IoT, and Machine Learning
    Published: Singapore :Springer Singapore : : 2022.,
    Description: xxiv, 801 p. :ill. (some col.), digital ;24 cm.
    [NT 15003449]: Performance Analysis of Classifier for Chronic Kidney Disease Prediction Using SVM, DNN, and KNN -- Comparative Analysis of Machine Learning Techniques in Classification Cervical Cancer using Isolation Forest with ADASYN -- Computer-Aided Cataract Detection Using Random Forest Classifier -- COV-Doctor: A Machine Learning Based Scheme for Early Identification of COVID-19 in Patients -- Ovarian Cancer Prediction from Ovarian Cysts Based on TVUS Using Machine Learning Algorithms -- A Comprehensive Analysis of Most Relevant Features Causes Heart Disease using Machine Learning Algorithms -- Early Stage Detection of Heart Failure using Machine Learning Techniques -- Automatic License Plate Recognition System For Bangladeshi Vehicles Using Deep Neural Network -- Vulnerability Analysis and Robust Training with Additive Noise for FGSM attack on Transfer Learning based Brain Tumor Detection from MRI -- Performance Evaluation of Convolution Neural Network based Object Detection Model for Bangladeshi Traffic Vehicle Detection -- Hyperspectral Image Classification Using Factor Analysis and Convolutional Neural Networks -- A Convolutional Neural Network Model for Screening COVID-19 Patients Based on CT Scan Images -- Real-Time Face Recognition System for Remote Employee Tracking.
    Contained By: Springer Nature eBook
    Subject: Big data - Congresses. -
    Online resource: https://doi.org/10.1007/978-981-16-6636-0
    ISBN: 9789811666360
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W9439087 電子資源 11.線上閱覽_V 電子書 EB QA76.9.B45 I57 2021 一般使用(Normal) On shelf 0
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