Intelligent System Design

Name: Intelligent System Design | Proceedings of INDIA 2022
Brand: Springer
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Proceedings of INDIA 2022

Vikrant Bhateja K. V. N. Sunitha Yen-Wei Chen Yu-Dong Zhang(Editor)

Springer (Publisher)

1st Edition

Published on 27. October 2022

XXX, 581 pages

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978-981-19-4863-3 (ISBN)

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Vikrant Bhateja is the associate professor in the Department of ECE, SRMGPC, Lucknow (U.P.), and also the dean (Academics) in the same college. He is doctorate in ECE (Bio-Medical Imaging) with a total academic teaching experience of 18 years with around 180 publications in reputed international conferences, journals and online book chapter contributions, out of which 31 papers are published in SCIE indexed high impact factored journals. He has been instrumental in chairing/co-chairing around 30 international conferences in India and abroad as publication/TPC chair and edited 45 book volumes from Springer Nature as a corresponding/co-editor/author on date. He has delivered nearly 20 keynotes, invited talks in international conferences, ATAL, TEQIP and other AICTE sponsored FDPs and STTPs. He is Editor-in-Chief of IGI Global-International Journal of Natural Computing and Research (IJNCR) an ACM and DBLP indexed journal since 2017. He has guest edited special issues in reputed SCIE indexed journals under Springer Nature and Elsevier.

K. V. N. Sunitha completed her B.Tech. in ECE from ANU, M.Tech. in CS from REC Warangal in 1993 and Ph.D. in CSE from JNTU Hyderabad in 2006. She has 29 years of teaching experience and 13 years of research experience. She is working as Founder Principal, BVRIT Hyderabad College of Engineering for Women, Hyderabad, since August 2012. She received "Academic Excellence Award" by G. Narayanamma Institute of Technology & Science in 2005, "Best computer Science Engineering Teacher Award for the year 2007" by ISTE in 2008, "Best Faculty Award" in Academic Brilliance Awards, 2013 at New Delhi, "Distinguished Principal Award" by CSI Mumbai in 2017 at IIT Bombay, received Deewang Mehtha "Women in Education Award" in 2017. She was felicitated for outstanding contribution and achievements in the field of Engineering in Women Engineers Meet 29th Indian Engineering Congress, IEI held at Visveswaraiah Bhavan, Hyderabad on 18 December 2014. She received "Engineer of the year 2019 Award" by IEI, Telangana in 2019. She received "Acharya Ratna"-National Award for life-time achievement for the year by Indian servers in association with IT Association of AP, Telangana IT Association, in 2019. She has guided 9 Ph.Ds. and currently guiding 8 research scholars. She authored 5 text books, published more than 150 papers.

Yen-Wei Chen received the B.E. degree in 1985 from Kobe Univ., Kobe, Japan, the M.E. degree in 1987 and the D.E. degree in 1990, both from Osaka Univ., Osaka, Japan. He was a research fellow with the Institute for Laser Technology, Osaka, from 1991 to 1994. From October 1994 to March 2004, he was an associate professor and a professor with the Department of Electrical and Electronic Engineering, Univ. of the Ryukyus, Okinawa, Japan. He is currently a professor with the college of Information Science and Engineering, Ritsumeikan University, Japan. Heis also a visiting professor with the College of Computer Science, Zhejiang University, China. He was a visiting professor with the Oxford University, Oxford, UK, in 2003 and a visiting professor with Pennsylvania State University, USA, in 2010. His research interests include medical image analysis, computer vision and computational intelligence. He has published more than 300 research papers in a number of leading journals and leading conferences including IEEE Trans. image processing, IEEE Trans. SMC, pattern recognition. He has received many distinguished awards including ICPR2012 Best Scientific Paper Award, 2014 JAMIT Best Paper Award, Outstanding Chinese Oversea Scholar Fund of Chinese Academy of Science. He is/was a leader of numerous national and industrial research projects.

Yu-Dong Zhang received his Ph.D. degree from Southeast University, China, in 2010. He worked as postdoc from 2010 to 2012 and a research scientist from 2012 to 2013 at Columbia University, USA. He served as Professor from 2013 to 2017 in Nanjing Normal University, where he was the director and founder of Advanced Medical Image Processing Group in NJNU. From 2017, he served as Full Professor in Department of Informatics, University of Leicester, UK. His research interests are deep learning in communication and signal processing, medical image processing. He was included in "Most Cited Chinese researchers (Computer Science)" from 2015 to 2018. He won "Emerald Citation of Excellence 2017", and "MDPI Top 10 Most Cited Papers 2015". He was included in top scientist list in "Guide2Research". He is now the editor of Scientific Reports, Journal of Alzheimer"s Disease, International Journal of Information Management, etc. He is the senior member of IEEE and ACM. He has conducted and joined many successful academic grants and industrial projects, such as NSFC, NIH, EPSRC, etc.

Content

Intro
Conference Organization Commitees
Preface
Contents
Editors and Contributors
A Framework for Early Recognition of Alzheimer's Using Machine Learning Approaches
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Model Diagram
3.2 CatBoost Classifier
3.3 Model Evaluation
4 Environmental Setup
5 Results and Discussion
5.1 Accuracy
5.2 Precision
5.3 Recall
5.4 F1-Score
6 Conclusion and Future Direction
References
On the Studies and Analyzes of Facial Detection and Recognition Using Machine Learning Algorithms
1 Introduction
2 Related Study
3 Facial Detection and Recognition Methods
3.1 Machine Learning Approach
3.2 Deep Learning Approach
4 Implementation
4.1 Face Detection: Haar Cascade Detection Algorithm
4.2 Face Recognition: Local Binary Pattern Histogram (LBPH) Algorithm
4.3 Detection and Recognition by GoogLeNet
5 Results and Discussion
5.1 Haar Cascade Face Detection (Machine Learning Approach)
5.2 LBPH Face Recognition in Real Time (Machine Learning Approach)
5.3 GoogLeNet Image-Based Analysis (Deep Learning Approach)
6 Conclusion
References
IPL Analysis and Match Prediction
1 Introduction
2 Literature Survey
3 Proposed Methodology
3.1 Processing the Datasets
3.2 Match Analysis
3.3 Visualization
3.4 Match Prediction
3.5 User Interface Creation
4 Results and Discussion
5 Conclusion
References
Application of ANN Combined with Machine Learning for Early Recognition of Parkinson's Disease
1 Introduction
2 Literature Work
3 Methodology
4 Experimental Setup
5 Performance Analysis and Experimentation Results
6 Conclusion and Future Work
References
People Count from Surveillance Video Using Convolution Neural Net
1 Introduction
2 Literature Review
3 Dataset
4 Proposed Methodology
5 Results
6 Conclusion
References
Detection of Pneumonia and COVID-19 from Chest X-Ray Images Using Neural Networks and Deep Learning
1 Introduction
2 Related Work
3 CNN Architectures
4 Proposed CNN Model
5 Experimentation and Results
5.1 Dataset
5.2 Experiment Setup
5.3 Results
5.4 Performance Evaluation
6 Conclusion
References
Plant Leaf Disease Detection and Classification Using Deep Learning Technique
1 Introduction
2 Literature Survey
3 Proposed System Architecture
3.1 Image Acquisition
3.2 Image Preprocessing
3.3 Feature Extraction Using CNN
3.4 Detect and Classify Disease
4 Result and Analysis
5 Conclusion
References
Breast Mass Classification Using Convolutional Neural Network
1 Introduction
2 Related Works
3 Proposed Methodology
3.1 About Dataset
3.2 Architecture of CNN
4 Results and Discussion
5 Conclusions
References
Deep Generative Models Under GAN: Variants, Applications, and Privacy Issues
1 Introduction
2 Generative Adversarial Networks (GANs)
2.1 GAN Architecture
2.2 Objective Function
3 Existing Models and Applications
3.1 GAN Models
3.2 Applications
4 GANs in Privacy
4.1 Privacy in Data
4.2 Privacy in Model
5 Future Works
6 Conclusion
References
Fusion-Based Celebrity Profiling Using Deep Learning
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset
3.2 Evaluation Measure
3.3 Stylistic Features
3.4 Word Embedding
3.5 Method
4 Results and Discussion
5 Conclusion
References
DeepLeaf: Analysis of Plant Leaves Using Deep Learning
1 Introduction
2 Related Work
3 Methodology
3.1 Feature Extraction
3.2 CNN and VGG16
4 Results and Discussion
4.1 Comparative Analysis with Respect to Accuracy
5 Conclusion
References
Potential Assessment of Wind Power Generation Using Machine Learning Algorithms for Southern Region of India
1 Introduction
2 Wind Power Technology
3 Methodology
3.1 Linear Regression
3.2 Support Vector Regression
3.3 K-Nearest Neighbour Algorithm
3.4 Decision Trees Regression
4 Performance Indices
4.1 Mean Absolute Error (MAE)
4.2 Mean Square Error (MSE)
4.3 Root Mean Square Error (RMSE)
4.4 R2 Score
5 Results and Discussions
6 Conclusions
References
OCR-LSTM: An Efficient Number Plate Detection System
1 Introduction
1.1 Tesseract
1.2 Opencv
1.3 Lstm
2 Literature Review
2.1 Problem Statement
2.2 Objective
3 System Model
3.1 Conversion of RGB Image to Gray Scale Image
3.2 Bilateral Filter
3.3 Lstm
4 Results and Discussion
5 Conclusions
References
Artificial Neural Network Alert Classifier for Construction Equipments Telematics (CET)
1 Introduction
2 Related Works
3 Problem Statement
4 System Model
4.1 Problem Formulation
5 Proposed Design and Methodology
6 Results and Discussion
6.1 Data Set
6.2 Results
7 Conclusions
References
Hybrid Approach of Modified IWD and Machine Learning Techniques for Android Malware Detection
1 Introduction
2 Related Works
3 Proposed Modified Version of IWD Algorithm
3.1 Step 1: The Static Parameters and Dynamic Parameters are Initialized
3.2 Step 2: Modified Edge Selection Process
3.3 Step 3: Updating Velocity and Soil Values
3.4 Step 4: Reinforcement and Termination Phase
4 Feature Selection Procedure Using Modified IWD
5 Dataset Prepossessing and Experimental Environment
5.1 Dataset and Preprocessing
5.2 Experimental Environment
6 Performance Evaluation Matrix
7 Result and Discussions
8 Conclusion and Future Work
References
Intuitionistic Fuzzy 9 Intersection Matrix for Obtaining the Relationship Between Indeterminate Objects
1 Introduction
2 Preliminary Concepts
2.1 Intuitionistic Fuzzy Set
2.2 Intuitionistic Fuzzy Topological Spaces
2.3 Related Studies
3 Intuitionistic Fuzzy 9 Intersection Matrix
4 Application of the Proposed Definitions
4.1 Importance of the Proposed Definition
4.2 Intuitionistic Fuzzy 9 Intersection Matrix
5 Conclusion and Future Work
References
A Hybrid Model of Latent Semantic Analysis with Graph-Based Text Summarization on Telugu Text
1 Introduction
2 Related Work
3 Latent Semantic Analysis
4 Text Rank Algorithm
5 Proposed Algorithm
6 Evaluation and Experimental Results
7 Conclusion
References
A Combined Approach of Steganography and Cryptography with Generative Adversarial Networks: Survey
1 Introduction
2 Background Works
3 Advanced Techniques
4 Fallouts and Discussion
5 Conclusion
References
Real-Time Accident Detection and Intimation System Using Deep Neural Networks
1 Introduction
2 Literature Review
3 Methods
4 Results and Discussion
5 Conclusion
References
Design of Cu-Doped SnO2 Thick-Film Gas Sensor for Methanol Using ANN Technique
1 Introduction
2 Proposed Experiment
3 Result and Discussion
4 Conclusion
References
Detect Traffic Lane Image Using Geospatial LiDAR Data Point Clouds with Machine Learning Analysis
1 Introduction
2 Literature Survey
3 Proposed System
3.1 Land-Usage/Land-Coverage Change Analysis
4 Interpretation Concept
5 Conclusion and Future Scope
References
Classification of High-Dimensionality Data Using Machine Learning Techniques
1 Introduction
2 Related Work
3 Machine Learning Techniques
3.1 Naive Bayes Algorithm
3.2 Support Vector Machine (SVM)
3.3 K-Nearest Neighbor (KNN) Algorithm
3.4 Principal Component Analysis (PCA)
4 Proposed Model
5 Performance Evaluation Metrics
6 Result Analysis
7 Conclusion
References
To Detect Plant Disease Identification on Leaf Using Machine Learning Algorithms
1 Introduction
2 Related Work
3 Problem Statement
4 Dataset and Attributes
5 Application of the Outcomes
6 Result Analysis
7 Conclusion
References
Association and Correlation Analysis for Predicting the Anomaly in the Stock Market
1 Introduction
2 Related Work
3 Data Preparation
4 Methodology
4.1 Data Mining Association Rule
5 Results and Discussion
6 Conclusion
References
Early Identification of Diabetic Retinopathy Using Deep Learning Techniques
1 Introduction
1.1 Types of Diabetic Retinopathy
2 Literature Review
3 Methodology
4 Experimentation Setup
5 Dataset
6 Image Processing
6.1 Input Fundus Images
6.2 Gray Fundus Images
6.3 Gaussian Blur
7 Convolution Neural Network Models
7.1 Training Using ResNet50 and VGG16
8 Result
8.1 Result of ResNet50
8.2 Result of VGG16
8.3 Comparison of Results
9 Conclusion
10 Future Work
11 Competing Interest
References
Performance Evaluation of MLP and CNN Models for Flood Prediction
1 Introduction
2 Study Area
3 Methodology
3.1 Mlp
3.2 CNN
3.3 Evaluating Constraint
4 Results and Discussions
5 Conclusion
References
Bidirectional LSTM-Based Sentiment Analysis of Context-Sensitive Lexicon for Imbalanced Text
1 Introduction
2 Related Work
2.1 Classification of Sentiments
2.2 Techniques of Supervised Learning
2.3 Techniques with No Supervision
2.4 Techniques for Semi-Supervised Learning
2.5 Ensemble Techniques
3 Proposed Methodology
3.1 Bidirectional Long Short-Term Memory (BLSTM)
3.2 Calculating Sentiment Scores
3.3 Resolving the Issue of Class Imbalance
4 Experimental Study
4.1 The Experimental Environment
4.2 Results and Discussion
5 Conclusion
References
Improving Streamflow Prediction Using Hybrid BPNN Model Combined with Particle Swarm Optimization
1 Introduction
2 Study Area
3 Methodology
3.1 BPNN
3.2 PSO
4 Results and Discussion
5 Conclusion
References
Prediction of Pullout Resistance of Geogrids Using ANN
1 Introduction
2 Pullout Force
3 Artificial Neural Network (ANN)
3.1 Development of ANN Model
3.2 Application of Developed ANN Model
4 Calculations of Relative Contribution Factors
5 Conclusions
References
Simulation of Water Table Depth Using Hybrid CANFIS Model: A Case Study
1 Introduction
2 Study Area
3 Methodology
3.1 CANFIS
3.2 CANFIS-FA
4 Results and Discussions
5 Conclusion
References
Monthly Runoff Prediction by Support Vector Machine Based on Whale Optimisation Algorithm
1 Introduction
2 Study Area
3 Methodology
3.1 Support Vector Machine
3.2 Whale Optimisation Algorithm
4 Results and Discussion
5 Conclusion
References
Application of Adaptive Neuro-Fuzzy Inference System and Salp Swarm Algorithm for Suspended Sediment Load Prediction
1 Introduction
2 Study Area
3 Methodology
3.1 Adaptive Neuro-Fuzzy Inference System
3.2 SSA
4 Results and Discussions
5 Conclusion
References
Maturity Status Estimation of Banana Using Image Deep Feature and Parallel Feature Fusion
1 Introduction
2 Methodology
3 Result and Discussion
4 Conclusion
References
Application of a Combined GRNN-FOA Model for Monthly Rainfall Forecasting in Northern Odisha, India
1 Introduction
2 Study Area
3 Methodology
3.1 GRNN
3.2 FOA
4 Results and Discussion
5 Conclusion
References
Guided Image Filter and SVM-Based Automated Classification of Microscopy Images
1 Introduction
2 Proposed Automated Classification of Microcopy Images
2.1 Guided Image Filter (GIF)
2.2 Otsu Thresholding (OT)
2.3 Scale Invariant Feature Transform (SIFT)
2.4 Support Vector Machines (SVMs)
3 Results and Discussion
3.1 Performance Evaluation
3.2 Experimental Results
3.3 Discussions
4 Conclusion
References
Application of Machine Learning Algorithms for Creating a Wilful Defaulter Prediction Model
1 Introduction
2 Literature Review
3 Methodology
3.1 Prediction Model
3.2 Model Performance Measures
4 Analysis and Discussion
5 Conclusion
References
Design of Metamaterial-Based Multilayer Dual Band Circularly Polarized Microstrip Patch Antenna
1 Introduction
2 Antenna Design
3 Results
4 Conclusions
References
Heart Disease Prediction in Healthcare Communities by Machine Learning Over Big Data
1 Introduction
2 Literature Survey
3 Proposed System
4 Algorithm
4.1 Algorithm Process Flow
5 Implementation
6 Results
7 Conclusion
References
A Novel Twitter Sentimental Analysis Approach Using Naive Bayes Classification
1 Introduction
2 Literature Survey
3 Proposed Methodology
4 Functionality and Design
5 Conclusion and Future Work
References
Recognition and Adoption of an Abducted Child Using Haar Cascade Classifier and JSON Model
1 Introduction
2 Literature Survey
2.1 A Survey on Previous Papers
2.2 Challenges and Gaps Identified
3 Methodology
3.1 Dataset
3.2 System Architecture
3.3 Methods
4 Results and Discussions
5 Conclusion
References
Automatic Brain Tumor Detection Using Convolutional Neural Networks
1 Introduction
2 Present System
3 Proposed System
4 Methodology
4.1 Datasets
4.2 CNN-Based Algorithm Classification
5 Discussions
6 Conclusion
References
Deep Learning and Blockchain for Electronic Health Record in Healthcare System
1 Introduction
2 Related Work
2.1 Deep Learning for Healthcare
2.2 Drug Discovery
2.3 Alzheimer's Disease Prediction
2.4 Clinical Imaging
2.5 Blockchain for Healthcare
2.6 Block Chain Based Electronic Health Record
2.7 Healthcare IoT and Medical Devices
2.8 Secure Blockchain Technology and Deep Learning Disease Prediction
3 Conclusion
References
Artificial Neural Networks in Improvement of Spatial Resolution of Thermal Infrared Data
1 Introduction
2 Artificial Neural Networks
3 TIR Information Spatial Resolution Enhancement
3.1 Improvement of Spatial Resolution: Case 1
3.2 Improvement of Spatial Resolution Case 2
3.3 Improvement of Resolution
4 Results and Observations
5 Conclusion
References
Facial Micro-expression Recognition Using Deep Learning
1 Introduction
2 Literature Survey
3 Proposed System
3.1 Frames Extraction
3.2 Data Preprocessing
3.3 Interface and Class Label Prediction
3.4 Limitations
4 Proposed Algorithm
5 Results
6 Conclusion
References
Precision Agriculture with Weed Detection Using Deep Learning
1 Introduction
2 Review of Literature
3 Proposed Architecture and Methodology
3.1 Proposed Architecture
3.2 Proposed Methodology of the Work
4 Discussion on Experimental Investigations
4.1 Dataset
4.2 Discussion on Results
5 Conclusion
References
An Ensemble Model to Detect Parkinson's Disease Using MRI Images
1 Introduction
2 Literature Review
3 Materials and Methods
3.1 Dataset
3.2 Methodology
4 Experimental Results
5 Conclusion
References
Classification of Diabetic Retinopathy Using Deep Neural Networks
1 Introduction
2 Literature Study
3 Methodology
3.1 Dataset Description
3.2 Pre-processing
3.3 Training
4 Results
5 Conclusion
References
A Deep Learning Model for Stationary Audio Noise Reduction
1 Introduction
2 Literature Review
3 Proposed Methodology
4 Results and Discussion
5 Conclusion and Future Scope
References
Optimizing Deep Neural Network for Viewpoint Detection in 360-Degree Images
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Viewpoint Prediction Using Feature Map
3.2 Viewpoint Prediction Using Object Detection Model
4 Results and Discussion
5 Conclusion and Future Scope
References
ConvNet of Deep Learning in Plant Disease Detection
1 Introduction
2 Image Processing
2.1 Image Acquisition
2.2 Image Preprocessing
2.3 Image Segmentation
2.4 Feature Extraction
2.5 Detection and Classification
3 Deep Learning
4 Convolutional Neural Network
4.1 Data Collection Phase
4.2 Data Augmentation Phase
4.3 Data Detection and Classification Phase
5 Conclusion
References
Recognition of Iris Segmentation Using CNN and Neural Networks
1 Introduction
2 Related Works
3 Proposed System
3.1 Image Data
3.2 Grayscale Conversion
4 Determination of Center and Radius
5 Determining Outer Boundary of Iris
6 Calculating the Outer Boundary of the Circle
7 Segmentation
7.1 CNN
7.2 Neural Network
8 Conclusion
References
Popularity of Optimization Techniques in Sentiment Analysis
1 Introduction
2 Sentiment Analysis
2.1 Data Collection from Different Sources
2.2 Preparation of Text
2.3 Feature Extraction
2.4 Feature Optimization
2.5 Sentiment Classification and Detection
2.6 Final Output
3 Sentiment Analysis Using Optimization Techniques
4 Result and Discussion
5 Conclusion
References
Predominant Role of Artificial Intelligence in Employee Retention
1 Introduction
2 Literature Review
3 AI and Its Impact on Various Occupations
4 Research Methodology
5 Statistical Treatment of Data
6 Factor Analysis
7 R Statistics
8 Result
9 Discussion
10 Conclusions and Suggestions
References
Semantic Segmentation of Brain MRI Images Using Squirrel Search Algorithm-Based Deep Convolution Neural Network
1 Introduction
2 SSA-Based Deep Convolution Neural Network
3 Results and Discussion
4 Conclusion
References
Top Five Machine Learning Libraries in Python: A Comparative Analysis
1 Introduction
2 Overview of Machine Learning Libraries
2.1 Scikit-Learn
2.2 TensorFlow
2.3 Keras
2.4 PyTorch
2.5 Theano
3 Comparative Analysis of Machine Learning Libraries
4 Conclusions
References
A Novel Technique of Threshold Distance-Based Vehicle Tracking System for Woman Safety
1 Introduction
1.1 Global Positioning Systems (GPS)
1.2 Assisted GPS (AGPS)
2 Existing System
3 Proposed System
3.1 Architecture
3.2 Bus Tracking Mechanism
3.3 Protect Her
3.4 Trace Route for Vehicles in Threshold Distance
4 Experimental Results
5 Conclusions
References
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Intelligent System Design

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