Machine learning and computational intelligence techniques for data engineering : Proceedings of the 4th International Conference MISP 2022. Volume 2

Machine learning and computational intelligence techniques for data engineering : Volume 2 / Proceedings of the 4th International Conference MISP 2022. Pradeep Singh, Deepak Singh, Vivek Tiwari, Sanjay Misra, editors.

This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved w...

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Bibliographic Details
Corporate Author: International Conference on Machine Intelligence and Signal Processing
Other Authors: Singh, Pradeep (Editor), Singh, Deepak (Editor), Tiwari, Vivek (Editor), Misra, Sanjay (Editor)
Format: eBook
Language:English
Published: Singapore : Springer, 2023.
Series:Lecture notes in electrical engineering ; v. 998.
Subjects:
Machine learning > Congresses.
Signal processing > Congresses.
Machine learning
Signal processing
Electronic books.
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Online Access:Click for online access
Table of Contents:
  • Intro
  • Contents
  • About the Editors
  • A Review on Rainfall Prediction Using Neural Networks
  • 1 Introduction
  • 2 Literature Survey
  • 3 Theoretical Analysis of Survey and Discussion
  • 4 Conclusions
  • References
  • Identifying the Impact of Crime in Indian Jail Prison Strength with Statical Measures
  • 1 Introduction
  • 2 Related Work
  • 3 Methods and Materials
  • 3.1 Dataset
  • 3.2 Experimental Work
  • 3.3 Correlation Coefficient Between Two Random Variables
  • 4 Result and Discussion
  • 5 Conclusion
  • References
  • Visual Question Answering Using Convolutional and Recurrent Neural Networks
  • 1 Introduction
  • 2 Literature Survey
  • 3 Dataset Description
  • 4 Proposed Method
  • 4.1 Experiment 1
  • 4.2 Experiment 2
  • 5 Results and Analysis
  • 5.1 Experiment 1
  • 5.2 Experiment 2
  • 6 Conclusion
  • References
  • Brain Tumor Segmentation Using Deep Neural Networks: A Comparative Study
  • 1 Introduction
  • 2 Methodology
  • 2.1 2-Path Convolutional Neural Network
  • 2.2 Cascaded Architecture
  • 2.3 U-Net
  • 3 Empirical Studies
  • 3.1 Dataset
  • 3.2 Experiment Setup
  • 3.3 Data Preprocessing
  • 3.4 Performance Evaluation Metrics
  • 4 Visualization and Result Analysis
  • 4.1 Cascaded CNN
  • 4.2 U-Net
  • 5 Conclusions
  • References
  • Predicting Bangladesh Life Expectancy Using Multiple Depend Features and Regression Models
  • 1 Introduction
  • 2 Literature Review
  • 3 Proposed Methodology
  • 3.1 Data Preprocessing
  • 3.2 Regressor Relevant Theory
  • 3.3 Preformation Calculation
  • 4 Results and Discussions
  • 5 Conclusion and Future Work
  • References
  • A Data-Driven Approach to Forecasting Bangladesh Next-Generation Economy
  • 1 Introduction
  • 2 Literature Review
  • 3 Methodology
  • 4 Analysis and Results
  • 5 Conclusion and Future Work
  • References
  • A Cross Dataset Approach for Noisy Speech Identification
  • 1 Introduction
  • 2 Problem Statement
  • 3 Prior Work
  • 4 Experimental Setup
  • 4.1 Phoneme Detection rate
  • 4.2 Softmax Probability of Clean Speech and Noisy Speech
  • 4.3 Utterance Level Scoring
  • 5 Results
  • 6 Conclusion and Future Work
  • References
  • A Robust Distributed Clustered Fault-Tolerant Scheduling for Wireless Sensor Networks (RDCFT)
  • 1 Introduction
  • 2 Literature Review
  • 2.1 Classification of Fault Levels
  • 2.2 Redundancy Based Fault Tolerance in WSNs
  • 3 Proposed Work
  • 3.1 Network Model, Preliminaries, and Assumptions
  • 3.2 Fault Detection and Recovery
  • 3.3 Redundancy Check and Clustering in WSNs
  • 3.4 Selection of Cluster Head
  • 3.5 Algorithm Phase: Distributed Clustered Fault-Tolerant Scheduling
  • 3.6 Simulation Setup and Results
  • 4 Conclusion and Future Remarks
  • References
  • Audio Scene Classification Based on Topic Modelling and Audio Events Using LDA and LSA
  • 1 Introduction
  • 2 Related Work
  • 3 LSA and LDA
  • 3.1 Latent Semantic Analysis (LSA)

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