Note: Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Image Processing and Computer Vision -- Leveraging CNN and Transfer Learning for Classification of Histopathology Images -- 1 Introduction -- 1.1 Histopathological Image Analysis -- 1.2 Contributions of This Work -- 2 Related Works -- 3 Methodology and Workflow -- 3.1 Experimental Setup -- 3.2 Dataset -- 3.3 ResNet50 -- 3.4 Transfer Learning and Added Layers -- 3.5 Training and Testing -- 3.6 Evaluation Metrics -- 4 Results -- 4.1 Confusion Matrix: Type I Type II Errors -- 4.2 Precision, Recall, F1 and More -- 4.3 AUC Value -- 4.4 Accuracy Comparisons -- 5 Conclusion -- 6 Future Scope -- References -- Lane Detection and Distance Estimation Using Computer Vision Techniques -- 1 Introduction -- 2 Methodology -- 2.1 Data Collection -- 2.2 Camera Calibration -- 2.3 Object Detection of Traffic Sign and Cars -- 2.4 Lane Segmentation Along with Grids -- 3 Purpose -- 4 Major Research Findings -- 5 Discussion -- 6 Results -- 7 Conclusion and Future Research Work -- References -- Using Deep Transfer Learning to Predict Student Engagement in Online Courses -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 Transfer Learning Using Pre-trained Networks -- 3.2 Extract Image Features Using Pre-trained Network -- 3.3 Contributions of Training and Testing Image Datasets -- 4 Results and Discussion -- 5 Conclusion -- References -- Performance Analysis of First Order Optimizers for Plant Pest Detection Using Deep Learning -- 1 Introduction -- 2 Optimization for Deep Learning -- 3 Gradient Based Optimizers -- 3.1 Gradient Descent (GD) -- 3.2 Stochastic Gradient Descent (SGD) -- 3.3 ADAGRAD -- 3.4 RMSPROP -- 3.5 ADAM -- 4 Methodology -- 4.1 Pest Dataset -- 5 Evaluation Metrics -- 6 Results and Discussion -- 7 Conclusion -- References. , A Review on Skin Pigment and Vein Pattern Detection Techniques -- 1 Introduction -- 1.1 Author's Contribution -- 1.2 Organization of the Paper -- 2 Literature Review -- 3 Skin Texture Analysis -- 4 Preprocessing -- 5 Discussion and Result -- 6 Conclusion -- 7 Future Work -- References -- Brain Tumor Classification Using Deep Learning Techniques -- 1 Introduction -- 1.1 Image Segmentation and MRI -- 1.2 Upcoming Sections -- 2 Background and Related Works -- 2.1 Related Research Work -- 2.2 Existing Methods for Brain Tumor Classification -- 3 Proposed Methodology -- 3.1 Dataset Used -- 3.2 Dataset Management -- 3.3 Model Used - RESNET 50 -- 4 Performance Analysis and Results -- 4.1 Running Different ResNet Models -- 4.2 Plotting Different Graphs for Analysis -- 4.3 Tumor Detection -- 5 Conclusion and Future Work -- References -- Automatic Image Caption Generation Using ResNet & -- Torch Vision -- 1 Introduction -- 2 Related Works -- 3 Proposed Work -- 4 Experimental Result -- 5 Conclusion and Future Scope -- References -- Consistency Comparison of Machine Vision Images Based on Improved ORB Algorithm -- 1 Introduction -- 2 Related Theoretical Overview and Research -- 2.1 Design and Research of Machine Vision Measuring System -- 2.2 Theoretical Introduction of Improved ORB Algorithm -- 3 Experiment and Research -- 3.1 Experimental Method -- 3.2 Experimental Requirements -- 4 Analysis and Discussion -- 4.1 Consistency and Accuracy Analysis of Machine Vision Image Based on ORB Algorithm -- 4.2 Accuracy Analysis of Machine Vision Image Consistency System -- 5 Conclusions -- References -- Application Analysis of Digital Special Effects Technology in Film and Television Post-production Based on Neural Network Algorithm -- 1 Introduction. , 2 Research on the Application of Digital Special Effects Technology in Film and Television Post-production Based on Neural Network Algorithm -- 2.1 Traditional Special Effects and 3D Digital Special Effects -- 2.2 Digital Technology Used in Film and Television Post-production -- 2.3 Neural Networks -- 3 Investigation and Research on the Application of Digital Special Effects Technology in Film and Television Post-production Based on Neural Network Algorithm -- 3.1 3D Human Reconstruction Digital Effects Technology Based on Neural Network -- 3.2 Data Set -- 4 Analysis and Research on the Application of Digital Special Effects Technology in Film and Television Post-production Based on Neural Network Algorithm -- 4.1 Network Structure of Digital Special Effects Technology for Human Reconstruction -- 4.2 Experimental Results -- 5 Conclusions -- References -- Video Image Analysis of Sports Skill Training on Account of Fuzzy Clustering Algorithm -- 1 Introduction -- 2 Research on the Application of Sports Skill Training Video Image Analysis Based on Fuzzy Clustering Algorithm -- 2.1 Based on Fuzzy Clustering Algorithm -- 2.2 Application of Sports Skill Training Video Image Analysis -- 3 Research on the Application Effect of Sports Skill Training Video Image Analysis Based on Fuzzy Clustering Algorithm -- 3.1 Content Analysis Method -- 3.2 Brief Description -- 3.3 The Formula -- 3.4 Calculation Principles -- 4 Investigation and Research on the Application of Sports Skill Training Video Image Analysis Based on Fuzzy Clustering Algorithm -- 4.1 Test Effect -- 5 Conclusions -- References -- Real Estate Display System Based on Virtual Reality Technology -- 1 Introduction -- 2 Real Estate 3D Modeling and System Requirements Analysis -- 2.1 3D Modeling of Real Estate -- 2.2 Non-functional Requirements for System Design -- 2.3 2D and 3D Model Data Association. , 3 System Design -- 3.1 System Build Tools -- 3.2 System Function Design -- 4 System Testing and Implementation -- 4.1 System Test -- 4.2 Implementation of System Roaming Interaction -- 5 Conclusion -- References -- Production of Film and Television Animation Based on Three -Dimensional Models Based on Deep Image Sequences -- 1 Introduction -- 2 Related Theoretical Overview and Research -- 2.1 Three -Dimensional Model Film and Television Animation Production Development Process -- 2.2 Theoretical Introduction to Depth Image Sequence -- 3 Experiment and Research -- 3.1 Experimental Method -- 3.2 Experimental Requirements -- 4 Analysis and Discussion -- 4.1 Analysis of the Exposure of the Film and Television Animation of 3D Model -- 4.2 Analysis of the Clarity of the Film and Television Animation of 3D Model and Economic Applicability -- 5 Conclusions -- References -- 3D Printing Design Simulation of Ceramic Products Based on 3D Image Reproduction Technology -- 1 Introduction -- 2 Image Based 3D Reconstruction Technology -- 3 Research on 3D Printing Design Simulation of Ceramic Products -- 3.1 Selection of Test Materials -- 3.2 Design Requirements for Slurry Extrusion Device of 3D Printer -- 3.3 3D Ceramic Printing Simulation Algorithm -- 4 Research on 3D Printing Design Simulation of Ceramic Products -- 5 Conclusions -- References -- Artificial Intelligence of Internet of Things and Virtual Reality Technology in the Image Reconstruction of Film and Television Characters -- 1 Introduction -- 2 Design and Research on the Image Reconstruction Research of Internet of Things Artificial Intelligence and Virtual Reality Technology in the Role Shaping of Film and Television Characters -- 2.1 The Internet of Things -- 2.2 Artificial Intelligence -- 2.3 Virtual Reality Technology. , 2.4 Research on Image Reconstruction of Internet of Things Artificial Intelligence and Virtual Reality Technology in Film and Television Character Shaping -- 3 Research on the Effect of Internet of Things Artificial Intelligence and Virtual Reality Technology in the Image Reconstruction of Film and Television Characters -- 3.1 Research on Image Reconstruction of Internet of Things Artificial Intelligence and Virtual Reality Technology in Film and Television Character Shaping -- 4 Investigation and Research Analysis of the Image Reconstruction of Internet of Things Artificial Intelligence and Virtual Reality Technology in the Role Shaping of Film and Television Characters -- 5 Conclusions -- References -- Research on the Application of Virtual Reality Technology in Environmental Art Design -- 1 Introduction -- 2 Stereoscopic Display Technology of Virtual Reality -- 3 Haptic Feedback Technology of Virtual Reality -- 4 Interactive Technology of Virtual Reality -- 5 Application of VR in Environmental Art Design -- 6 Conclusion -- References -- Computer Vision and Pattern Recognition Technology on Account of Deep Neural Network -- 1 Introduction -- 2 Design and Exploration of Application Construction of Computer Vision and Pattern Recognition Technology on Account of Deep Neural Network -- 2.1 Deep Neural Network Algorithm -- 2.2 Application of Computer Vision and Pattern Recognition Technology on Account of Deep Neural Network -- 3 Exploring the Application Effect of Computer Vision and Pattern Recognition Technology on Account of Deep Neural Network -- 3.1 The Popularization and Application of Computer Vision Technology -- 4 Investigation and Research on Application of Computer Vision and Pattern Recognition Technology on Account of Deep Neural Network. -- 5 Conclusions -- References. , Design of 3D Image Visual Communication System Based on Computer Image Technology.

Note: Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Machine Learning and Computational Intelligence -- Cardiac Arrhythmia Classification Using Cascaded Deep Learning Approach (LSTM & -- RNN) -- 1 Introduction -- 2 Deep Learning Techniques -- 2.1 Convolutional Neural Network (CNN) -- 2.2 Recurrent Neural Network -- 2.3 Long Short-Term Memory (LSTM) -- 2.4 Gated Recurrent Unit (GRU) -- 3 Proposed Work and Methodology -- 4 Experimental Setup -- 5 Result and Future Scope -- References -- A Computational Approach to Identify Normal and Abnormal Persons Gait Using Various Machine Learning and Deep Learning Classifier -- 1 Introduction -- 2 Related Work -- 3 Data Acquisition -- 4 Proposed Method -- 5 Result Evaluation -- 6 Conclusion and Future Work -- References -- Hierarchical-Based Binary Moth Flame Optimization for Feature Extraction in Biomedical Application -- 1 Introduction -- 2 Related Work -- 3 Proposed HBMFO Model -- 3.1 Moth Flame Optimization (MFO) -- 3.2 Hierarchical Binary MFO (HBMFO) -- 3.3 Evaluation -- 4 Results and Discussions -- 5 Conclusion -- References -- Distinctive Approach for Speech Emotion Recognition Using Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Scheme -- 3.1 Data Collection -- 3.2 Visualization -- 3.3 Augmentation -- 3.4 Feature Extraction -- 3.5 Classification Approaches -- 4 Experimental Analysis -- 5 Conclusion -- References -- A Survey on Human Activity Recognition Using Deep Learning Techniques and Wearable Sensor Data -- 1 Introduction -- 2 Overview of Human Activity Recognition -- 2.1 Data Acquisition -- 2.2 Data Segmentation -- 2.3 Feature Extraction and Classification -- 3 Wearable Sensors -- 3.1 Inertial Measurement Unit (IMU) -- 3.2 Electromyography (EMG) -- 3.3 Electrocardiography (ECG) -- 3.4 Electroencephalography (EEG). , 4 Applications of HAR Using Wearable Sensor Data -- 5 Datasets -- 5.1 UCI-HAR -- 5.2 PAMAP2 -- 5.3 WISDM -- 5.4 MHEALTH -- 5.5 Opportunity -- 5.6 Daphnet -- 6 Deep Learning Techniques Applied for HAR in Literature -- 6.1 Autoencoder -- 6.2 CNN -- 6.3 Recurrent Neural Network (RNN) -- 6.4 Deep Belief Network (DBN) -- 7 Challenges and Future Scope -- 8 Conclusions -- References -- Refined-Para Forming Question Generation System Using Lamma -- 1 Introduction -- 2 Related Work -- 3 Problem Definition -- 3.1 Important Flow Steps -- 4 Implementation Details -- 5 Results and Discussion -- 5.1 Evaluation -- 6 Objective Evaluation -- 7 Conclusion -- 8 Future Work -- References -- Estimation of Dynamic Balancing Margin of the 10-DOF Biped Robot by Using Polynomial Trajectories -- 1 Introduction -- 2 Mathematical Modelling of the Biped Robot -- 2.1 Forward Kinematics -- 2.2 Inverse Kinematics -- 2.3 Foot Trajectory -- 2.4 Dynamic Balance Margin (DBM) -- 3 Experimentation -- 4 Results and Discussion -- 5 Conclusions -- 6 Future Scope -- References -- A Review on: Deep Learning and Computer Intelligent Techniques Using X-Ray Imaging for the Early Detection of Knee Osteoarthritis -- 1 Introduction -- 2 Literature Review -- 3 Comparative Analysis -- 3.1 Region of Interest (ROI) and Segmentation -- 3.2 Deep Learning -- 3.3 As a Feature Descriptor, Convolutional Neural Network -- 3.4 Oriented Gradient Histogram -- 3.5 Pattern of Local Binary -- 4 Experimental Evaluation -- 4.1 Dataset -- 4.2 State of Art Comparisons -- 5 Conclusion -- References -- Effective Real Time Disaster Management Using Optimized Scheduling -- 1 Introduction -- 1.1 Real Time Scheduling for Disaster Management -- 2 Background Work -- 3 Methodology -- 4 Implementation -- 4.1 Case Study of Flash Flood Crisis Management -- 4.2 Disaster Management System Model. , 4.3 Cluster Based Scheduling Algorithm -- 5 Result and Discussion -- 6 Conclusions -- References -- Design System of Urban Residential Environment Based on Interactive Genetic Algorithm -- 1 Introduction -- 2 Research on the Optimal Design System of Urban Living Environment Based on Interactive Genetic Algorithm -- 2.1 The Role of Interactive Genetic Algorithm in the Optimization of Urban Living Environment -- 2.2 Problems Existing in the Urban Living Environment -- 2.3 Establishment of the Fitness Function -- 2.4 Algorithm Process -- 3 System Design Experiment of Optimization Design of Urban Living Environment Based on Interactive Genetic Algorithm -- 3.1 Residential Environment Survey -- 3.2 Simulation System Operation -- 4 Experimental Analysis of the Systematic Optimization Design of Urban Living Environment Based on Interactive Genetic Algorithm -- 4.1 Factors and Analysis of Resident Satisfaction -- 4.2 Program Satisfaction Analysis -- 5 Conclusions -- References -- Sensorless Control Algorithm of Permanent Magnet Synchronous Motor on Account of Neural Network -- 1 Introduction -- 2 Design and Exploration of Sensorless Control Algorithm of Permanent Magnet Synchronous Motor on Account of Neural Network -- 2.1 Neural Network Algorithm -- 2.2 Sensorless Control Algorithm of Permanent Magnet Synchronous Motor Based on Neural Network -- 3 Research on the Effect of Sensorless Control Algorithm of Permanent Magnet Synchronous Motor on Account of Neural Network -- 4 Investigation and Research on Sensorless Control Algorithm of Permanent Magnet Synchronous Motor on Account of Neural Network -- 5 Conclusions -- References -- A Techno Aid to Ease in e-Rehabilitation -- 1 Introduction -- 2 Role of Assistive Technology (AT) and Rehabilitative Technology (RT) in Rehabilitation -- 3 AT and RT Related Technologies for Patient Connectivity with Society. , 3.1 Robotic Technology in Rehabilitation -- 3.2 Wearable Technology in Rehabilitation -- 3.3 Virtual Reality Technology in Rehabilitation -- 3.4 Internet of Things (IoT) Technology in Rehabilitation -- 4 System Model for Patient Monitoring System -- 4.1 Keeping Track of Patient Conditions -- 4.2 Collection of Patient's Heath Parameters -- 4.3 Interact with Patient -- 4.4 Patient's Security -- 4.5 Remote Patient's Monitoring -- 5 Methodology and Implementation Details -- 5.1 Design an IoT Framework -- 5.2 Connecting and Storing Data on Cloud -- 5.3 Website Application -- 6 System Working Model Flowchart -- 7 Results and Analysis -- 8 Conclusion -- References -- A Novel Approach to Analyse Lung Cancer Progression and Metastasis Using Page Rank Technique -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset Description -- 2.2 PageRank Algorithm -- 3 Results and Discussion -- 4 Conclusion -- References -- Homomorphic Encryption of Neural Networks -- 1 Introduction -- 2 Literature Survey -- 2.1 Homomorphism -- 2.2 Partially Homomorphic Systems -- 2.3 Additive Homomorphic Systems -- 2.4 Multiplicative Homomorphic Systems -- 2.5 Additive and Multiplicative Homomorphic Encryption Systems -- 2.6 Somewhat Homomorphic Encryption -- 2.7 Fully Homomorphic Encryption Systems -- 2.8 Encryption Scheme -- 3 Proposed Algorithm and Its Application -- 3.1 Applications -- 3.2 Medical Records -- 3.3 Finance and Advertising -- 3.4 Neural Network Support -- 3.5 Support for Floating Point Numbers -- 3.6 Encrypting Neural Network -- 4 Result and Analysis -- 5 Conclusion and Future Work -- References -- An Empirical Study to Enhance the Accuracy of an Ensemble Learning Model for Crop Recommendation System by Using Bit-Fusion Algorithm -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Dataset Preparation -- 3.2 Study Area. , 3.3 The Importance of the Base Classifier -- 4 Results of Experimental Assessment and Simulation -- 4.1 Ada Boost Classifier Simulation Results -- 4.2 Gradient Boosting Simulation Results -- 4.3 XGB Classifier Simulation Results -- 5 Proposed Algorithm based on SVM and CNN -- 5.1 Ensemble Method (SVM + CNN) -- 5.2 Description of the Bit-Fusion Algorithm -- 5.3 Comparison Between Proposed Bit-Fusion Ensemble Technique vs Traditional Fusion Methods -- 6 Conclusion and Future Scope -- References -- Bayesian Learning Model for Predicting Stability of System with Nonlinear Characteristics -- 1 Introduction -- 2 Gathering Data for the ML Model -- 3 Bayesian Learning for Machining Stability -- 4 Learning Stability with Non-linear Characteristics -- 4.1 Learning Stability for a Process Exhibiting Bistable Behaviour -- 4.2 Learning Stability with Process Damping -- 5 Conclusion -- References -- Data Sciences -- Novel ABC: Aspect Based Classification of Sentiments Using Text Mining for COVID-19 Comments -- 1 Introduction -- 2 Related Work -- 3 Text Mining: The Process -- 3.1 Steps in Text Mining -- 4 Classification of Sentiments for Text-Based Content -- 5 Frequently Used Methods and Techniques -- 5.1 Basic Methods -- 5.2 Advanced Methods -- 6 Proposed Methodology -- 6.1 Steps for Novel ABC: Aspect Based Classification -- 7 Results and Analysis -- 7.1 Comparative Analysis -- 8 Conclusions and Future Work -- References -- Topic Modeling, Sentiment Analysis and Text Summarization for Analyzing News Headlines and Articles -- 1 Introduction -- 2 Related Work -- 2.1 Topic Modeling -- 2.2 Sentiment Analysis and Emotion Detection -- 2.3 Topic Modeling and Sentiment Analysis -- 2.4 Text Summarization and Other Approaches -- 3 Methodology -- 3.1 Module 1: Topic Modeling -- 3.2 Module 2: Text Summarization -- 3.3 Module 3: Sentiment Classification. , 4 Results and Experiments Discussion.