Note: 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.