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Format: 1 Online-Ressource (482 Seiten)

Edition: 1st ed

ISBN: 9783031230929

Series Statement: Communications in Computer and Information Science Series v.1759

Note: Description based on publisher supplied metadata and other sources , Intro -- Preface -- Organization -- Abstracts of Keynotes -- Post-pandemic Applications of AI and Machine Learning -- Smart and Soft Computing Methods for Prioritizing Software Requirements in Large-Scale Software Projects -- Your Readiness for Industry 4.0 -- Securing NexGen Automotives - Threats and Trends -- Cyber Attacks Classification and Attack Handling Methods Using Machine Learning Methods -- The Internet of Things (IoT) Ecosystem Revolution in the World of Global Sports -- Orchestration of Containers: Role of Artificial Intelligence -- Enterprise Cybersecurity Strategies in the Cloud -- Contents - Part I -- Contents - Part II -- Artificial Intelligence -- Galaxy Classification Using Deep Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Dataset Collection -- 3.2 Proposed Deep Galaxies CNN Model -- 3.3 Overview of Algorithms -- 4 Comparative Results -- 4.1 Model Accuracy -- 5 Conclusion and Future Scope -- References -- Word Sense Disambiguation for Hindi Language Using Neural Network -- 1 Introduction -- 2 Related Work -- 2.1 Background -- 2.2 Variants of Word Sense Disambiguation Work -- 2.3 Existing Approaches for Disambiguation -- 3 Proposed Approach for WSD -- 3.1 Architecture of the Proposed WSD Model -- 3.2 Implementation Details -- 4 Result Discussion -- 5 Conclusion and Future Directions -- References -- Social Media Addiction: Analysis on Impact of Self-esteem and Recommending Methods to Reduce Addiction -- 1 Introduction -- 2 Related Work -- 3 Measures -- 3.1 Bergen Social Media Addiction Scale (BSMAS) [5] -- 3.2 Rosenberg Self-esteem Scale (RSES) [5] -- 3.3 Recommendation Methods [14, 15] -- 3.4 Dataset Collection 1 -- 3.5 Dataset Collection 2 -- 4 Proposed Methodology -- 4.1 Statistical Analysis -- 4.2 Recommendation System -- 5 Results and Discussion -- 5.1 Statistical Analysis , 5.2 Recommendation System -- 6 Conclusion -- References -- A Combined Method for Document Image Enhancement Using Image Smoothing, Gray-Level Reduction and Thresholding -- 1 Introduction -- 2 Types of Noises -- 2.1 Speckle Noise -- 2.2 Gaussian Noise -- 2.3 Salt and Pepper Noise -- 3 Proposed Work for Document Image Enhancement -- 3.1 Edge Preserving Image Smoothing -- 3.2 Gray Level Reduction -- 3.3 Image Thresholding Using Otsu's Method -- 4 Experimentation and Results -- 5 Conclusions and Future Work -- References -- A Comparative Assessment of Deep Learning Approaches for Opinion Mining -- 1 Introduction -- 2 Literature Review -- 3 Tools for Opinion Mining -- 4 Deep Learning Techniques -- 4.1 Convolutional Neural Network (CNN) -- 4.2 Recurrent Neural Network (RNN) -- 4.3 Long Short Term Memory (LSTM) -- 4.4 Deep Neural Networks (DNN) -- 4.5 Deep Belief Networks (DBN) -- 4.6 Recursive Neural Network (RECNN) -- 4.7 Hybrid Neural Network -- 5 System Architecture -- 6 Advantages of Deep Learning -- 7 When to Use Deep Learning -- 8 Disadvantages of Deep Learning -- 9 Conclusion -- References -- Performance Enhancement in WSN Through Fuzzy C-Means Based Hybrid Clustering (FCMHC) -- 1 Introduction -- 2 Related Work -- 3 Network Model -- 3.1 Radio Model -- 3.2 Assumptions -- 4 Proposed Algorithm -- 4.1 Cluster Formation Phase -- 4.2 Cluster Head Selection Phase -- 4.3 Communication Phase -- 5 Analytical Evaluation of Performance -- 5.1 Performance Metrics -- 5.2 Simulation Parameters -- 5.3 Results and Discussion -- 6 Conclusion -- References -- A Review of Gait Analysis Based on Age and Gender Prediction -- 1 Introduction -- 2 Gait Analysis and Feature Extraction -- 2.1 Gait and Gait Cycle -- 2.2 Gait and Gait Cycle -- 2.3 Gait and Gait Cycle -- 2.4 Motivation and Application of GEI Motivation -- 3 Evolution Metric -- 4 Related Work , 5 Comparison and Summary of Related Research Work -- 6 Future Work -- 7 Limitations and Challenges -- 8 Conclusion -- References -- Handwritten Signature Verification Using Convolution Neural Network (CNN) -- 1 Introduction -- 1.1 About the Domain -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Converting Image to Binary -- 3.2 Noise Removal -- 3.3 Image Enlargement -- 4 Feature Extraction -- 5 Feature Selection -- 6 Classification -- 7 Conclusion and Future Work -- References -- Comparative Analysis of Energy Consumption in Text Processing Models -- 1 Introduction -- 2 Existing Approaches -- 3 Exploration of the Data-Set -- 3.1 Average Word Length -- 3.2 Average Character Length -- 3.3 Number of Comments -- 4 Modelling -- 4.1 Simple Machine Learning Model -- 4.2 DistilBERT Model -- 4.3 Conv1D Model -- 4.4 Gated Recurrence Unit - GRU Model -- 5 Results -- 6 Conclusion -- References -- Evolution Towards 6G Wireless Networks: A Resource Allocation Perspective with Deep Learning Approach - A Review -- 1 Introduction -- 1.1 6G Vision -- 1.2 Technical Objectives of 6G -- 2 Resource Allocation for 6G Wireless Networks -- 3 Summary of Deep Learning Algorithms Used for 6G Wireless Networks Resource Allocation -- 4 Conclusion and Future Scope -- Appendix -- References -- Automation of Rice Leaf Diseases Prediction Using Deep Learning Hybrid Model VVIR -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 Results -- 5 Discussion -- References -- A Review Based on Machine Learning for Feature Selection and Feature Extraction -- 1 Introduction -- 2 Preliminaries -- 2.1 Feature Selection -- 2.2 Reducing the Dimensionality -- 3 Related Works -- 3.1 Feature Selection Approaches -- 3.2 Feature Extraction Approaches -- 4 Discussion -- 5 Conclusion -- References -- Automating Scorecard and Commentary Based on Umpire Gesture Recognition -- 1 Introduction , 2 Literature Survey -- 3 Methodology -- 3.1 Umpire Gestures -- 3.2 Dataset -- 3.3 Feature Extraction -- 3.4 Classification of Umpire Gestures -- 3.5 Scorecard Updating Feature -- 4 Results and Discussion -- 5 Conclusion -- References -- Rating YouTube Videos: An Improvised and Effective Approach -- 1 Introduction -- 2 Previous Work -- 3 Implementation -- 3.1 Comment Collection and Preprocessing -- 3.2 Sentiment Measure -- 3.3 Word Cloud -- 3.4 Video Rating -- 4 Performance Review of Proposed Approach -- 4.1 Major Application: Detection of Clickbait Videos -- 5 Limitations and Loopholes -- 6 Result -- 7 Conclusion -- 8 Future Work -- References -- Classification of Tweet on Disaster Management Using Random Forest -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Preprocessing -- 3.2 Training, Validation and Testing -- 3.3 Feature Extraction -- 3.4 Random Forest Classification -- 3.5 Location Extraction -- 4 Results and Discussions -- 5 Datasets -- 6 Experiment -- 7 Validation -- 8 Conclusions -- References -- Numerical Investigation of Dynamic Stress Distribution in a Railway Embankment Reinforced by Geogrid Based Weak Soil Formation Using Hybrid RNN-EHO -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Model Clay Barrier's Compositional Characteristics -- 2.2 Geogrid -- 2.3 Measuring Subgrade Stiffness -- 2.4 Multi Objective Function -- 2.5 Improving Settlement-Based Geogrid using Hybrid RNN-EHO Technique -- 2.6 The Procedure of the EHO in Realizing the Learning of RNN -- 3 Results and Discussion -- 3.1 Uncertainty Analysis -- 4 Conclusion -- References -- Efficient Intrusion Detection and Classification Using Enhanced MLP Deep Learning Model -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 4 Results and Discussion -- 5 Conclusion -- References , Classification of Medical Datasets Using Optimal Feature Selection Method with Multi-support Vector Machine -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Results and Discussions -- 5 Conclusions -- References -- Predicting Students' Outcomes with Respect to Trust, Perception, and Usefulness of Their Instructors in Academic Help Seeking Using Fuzzy Logic Approach -- 1 Introduction -- 2 Literature Review -- 3 Proposed Work -- 4 Results and Discussions -- 5 Conclusion -- References -- Smart Computing -- Automatic Cotton Leaf Disease Classification and Detection by Convolutional Neural Network -- 1 Introduction -- 2 Literature Review -- 3 List of Cotton Diseases -- 4 Materials and Methods -- 4.1 Dataset and Data Augmentation -- 4.2 CNN Pre-trained Architectures -- 4.3 Classification by Proposed CNN -- 5 Results and Discussions of Research -- 5.1 Pre-trained Model -- 6 Conclusion -- References -- Analytical Review and Study on Emotion Recognition Strategies Using Multimodal Signals -- 1 Introduction -- 2 Literature Survey -- 2.1 Classification of Emotion Recognition Strategies -- 3 Research Gaps and Issues -- 4 Analysis and Discussion -- 4.1 Analysis with Respect to Publication years -- 4.2 Analysis on the Basis of Strategies -- 4.3 Analysis on the Basis of Implementation Tool -- 4.4 Analysis in Terms of Employed Datasets -- 4.5 Analysis on the Basis of Evaluation Measures -- 4.6 Analysis Using Evaluation Measures Values -- 5 Conclusion -- References -- An Image Performance Against Normal, Grayscale and Color Spaced Images -- 1 Introduction -- 2 Overview of Image Matching Techniques -- 2.1 SIFT -- 2.2 SURF -- 2.3 ORB -- 3 Experimental Results -- 3.1 L*A*B* Color Space -- 4 Conclusion -- References -- Study of X Ray Detection Using CNN in Machine Learning -- 1 Introduction -- 2 Literature Review -- 2.1 Methods , 3 Algorithm CNN Model Algorithm Model = Sequential()

Additional Edition: Erscheint auch als Druck-Ausgabe Rajagopal, Sridaran Advancements in Smart Computing and Information Security Cham : Springer,c2023 ISBN 9783031230912

Language: English