Proceedings of the International Conference on Big Data, IoT, and Machine Learning BIM 2021

This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and mac...

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Bibliographic Details
Other Authors: Arefin, Mohammad Shamsul (Editor), Kaiser, M. Shamim (Editor), Bandyopadhyay, Anirban (Editor), Ahad, Md. Atiqur Rahman (Editor)
Format: eBook
Language:English
Published: Singapore Springer Nature Singapore 2022, 2022
Edition:1st ed. 2022
Series:Lecture Notes on Data Engineering and Communications Technologies
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 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