Proceedings of International Conference on Intelligent Vision and Computing (ICIVC 2023) : Volume 2

• Record Nr.: UNINA9910899892203321
• Autore: Saha Apu Kumar
• Pubbl/distr/stampa: Cham : , : Springer, , 2024; ©2024
• ISBN: 9783031713880; 3031713885
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (343 pages)
• Collana: Proceedings in Adaptation, Learning and Optimization Series ; ; v.19
• Altri autori (Persone): SharmaHarish; PrasadMukesh
• Soggetti: Computational intelligence; Machine learning
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- Preface -- Contents -- FashionWhiz: A Novel Realtime Virtual Fashion Recommender with Try-On Feature -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Fashion Recommendation System -- 3.2 Fashion Customization -- 3.3 Virtual Try-On -- 4 Observations and Result -- 4.1 Fashion Recommendation System -- 4.2 Fashion Customization -- 4.3 Virtual Try On -- 5 Future Enhancement -- 6 Conclusion -- References -- An Efficient Intrusion Detection Systems in the IoT and Its Challenges: A Critical Review -- 1 Introduction -- 2 Background Details -- 2.1 IoT Intrusion Detection System -- 2.2 Supervised Learning -- 2.3 Unsupervised Learning -- 2.4 IDS Verification Techniques -- 2.5 IoT Ecosystem's Threats -- 3 Literature Review -- 4 Conclusion -- References -- Artificial Intelligence in the Detection of Autism Spectrum Disorders (ASD): a Systematic Review -- 1 Introduction -- 1.1 Related Work -- 2 Methods -- 3 Results -- 3.1 Methods for Early Detection of ASD -- 3.2 AI and Socioemotional Development in Children with ASD -- 3.3 Technologies for Studying ASD in Children -- 4 Discussion and Conclusions -- References -- Revolutionizing Underwater Imaging: Unveiling the Impact and Advancements Enabled by the Keras UNet ; Family -- 1 Introduction -- 1.1 Challenges in Underwater Imaging -- 1.2 Objectives of this Work -- 2 Related Work -- 3 Methodology -- 3.1 Data Preparartion -- 3.2 Networks for Binary Segmentation -- 3.3 Proposed Methodology -- 3.4 Experimental Setup -- 4 Experimental Results -- 5 Conclusion and Future Scope -- References -- Trustworthy Machine Emotion Intelligence Using Facial Micro-expressions -- 1 Introduction -- 2 Systematic Literature Review: FME and Explainability -- 2.1 FME and CNNs -- 2.2 Technique Enhancements and Multimodality -- 2.3 Target Demographics and Dataset Challenges -- 2.4 Explainability and XAI in FME.; 2.5 Attention Mechanisms and Trustworthiness -- 3 Gaps in Literature and Paper Contribution -- 3.1 Gaps in Literature -- 3.2 Paper Contribution -- 4 Materials and Methods -- 4.1 Dataset Collection and Preprocessing -- 4.2 Facial Micro-expressions Used Models -- 4.3 Evaluation Metric Used -- 4.4 Explainable AI Techniques Used -- 4.5 Gradient-Weighted Class Activation Mapping (GradCAM) -- 4.6 Interpretations Through Occlusion Sensitivity -- 5 Model Performance and Discussions -- 5.1 ML Models -- 5.2 Explainability with LIME -- 5.3 Explainability with GradCAM -- 5.4 Explainabilty with Occlusion Sensitive -- 6 Conclusion and Future Work -- 6.1 Paper Conclusion -- 6.2 Intended Future Work -- References -- A Data Management System for a Uro-Oncology Medical Clinic -- 1 Introduction -- 2 Architecture and Data Model -- 2.1 Architecture -- 2.2 Data Model -- 3 Development of the Doubling Time Calculator -- 4 Calculator Development Prior to Radical Prostatectomy -- 5 Calculator Development After Radical Prostatectomy -- 6 Functionality -- 7 Conclusions and Future Work -- References -- Designing Energy Efficient Reinforcement Learning Based Routing Protocol for Next Generation Large Area WSN: EE-RLRP -- 1 Introduction -- 1.1 IoT-WSN Architecture -- 1.2 Challenges of Routing Protocols -- 1.3 Contribution of Work -- 2 Literature Review -- 3 Proposed EE-RLRP Designs -- 3.1 Proposed Methodology -- 4 Simulation Results and Discussions -- 4.1 Validation -- 4.2 Parametric Optimization -- 4.3 Impact of Density Over LA-WSN Performance -- 4.4 Comparison with Existing Protocols -- 5 Conclusions and Future Scope -- References -- COVID-19 Imposes Rethinking of Conferencing - Environmental Impact Assessment of Artificial Intelligence Conferences -- 1 Introduction -- 2 Materials and Methods -- 2.1 Selected Conferences -- 2.2 Considerations and Research Assumptions.; 2.3 Optimal Conference Location Selection Approaches -- 2.4 Overall Proposed Methodology -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Tackling Road Hazards: Classification and Detection of Crack and Potholes Using Deep Learning -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Dataset -- 3.2 Classification Workflow Using ResNet50 -- 3.3 Detection Workflow Using YOLOv8 -- 4 Results -- 5 Conclusion -- References -- ECPX: Empowering Commodity Price Prediction Using XGBoost Algorithm -- 1 Introduction -- 2 Related Approaches -- 3 Proposed System -- 3.1 Data and Variables -- 3.2 XGBoost Algorithm -- 3.3 System Design -- 4 Implementation and Results -- 5 Conclusion -- 5.1 Future Enhancement -- References -- HRIDAYA- A Cardiovascular Disease Prediction Model -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 System Architecture -- 3.2 Mathematical Algorithms -- 3.3 Model Algorithm -- 4 Testing -- 5 Results and Discussions -- 6 Conclusion -- References -- A Robust Smart Model for Detecting Hindi Fake News on Social Media Platforms Using Hybrid Deep Learning Approach -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 4 Results Analysis -- 5 Analysis of Experimental ; Results -- 6 Conclusion -- 7 Future Work -- References -- Sentiment Urgency Emotion Detection for Business Intelligence -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 A. Training the Sentiment Urgency Emotion Detection Model -- 4 Statement of Results and Analysis -- 5 Conclusion -- References -- Autism Spectrum Disorder Detection Using Facial Emotion Recognition Mechanism Based on Novel Hybrid DCNN and Optimized ECOC Technique -- 1 Introduction -- 2 Related Research Work -- 2.1 Autism Detection Using Facial Expressions -- 2.2 Human Emotion Detection Using CNN -- 3 Methodology -- 3.1 Classical CNN Model.; 3.2 Combination of CNN and ECOC Classifier -- 3.3 Proposed Model - CNN as a Feature Extractor and Optimize ECOC as a Classifier -- 4 Experimental Setup -- 4.1 Dataset Used -- 4.2 Feature Visualization -- 5 Results and Discussion -- 6 Conclusion -- References -- An Augmented Data Storage Algorithm for Digital Assistants Using Cryptography -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Algorithm -- 3.1 Text Encryption Model -- 3.2 Image Encryption Model -- 4 Implementation -- 4.1 Cryptographic Analysis -- 4.2 Computation Time Analysis -- References -- Survey on Deepfake Detection for Preventing Audio and Video Frauds Using Advanced Deep Learning Techniques -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Proposed System -- 4 Results -- 5 Limitations and Future Scope -- 6 Conclusion -- References -- Utilizing LLM and Deep Learning Strategies to Amplify Algorithmic Proficiency in Detecting Complex Patterns of Insider Trading Fraud -- 1 Introduction -- 2 Literature Review -- 3 Method Used -- 3.1 Data Extraction and Feature Engineering -- 3.2 Proposed Architecture -- 4 Results -- 5 Conclusion -- 6 Future Scope -- References -- Machine Learning-Based Water Potability Prediction: Model Evaluation, and Hyperparameter Optimization -- 1 Introduction -- 2 Literature Review -- 3 Data Acquisition -- 4 Data Preparation -- 4.1 Missing Values Handling -- 4.2 Dimensionality Reduction -- 4.3 Outlier Checking -- 4.4 Normalization -- 5 Model Training -- 5.1 Decision Tree Classifier -- 5.2 K-Nearest Neighbors -- 5.3 Random Forest Classifier -- 5.4 Logistic Regression -- 5.5 Stochastic Gradient -- 5.6 Support Vector Machine -- 5.7 Back Propagation Algorithm -- 6 Model Optimization and Evaluation -- 7 Prediction -- 8 Conclusion -- 9 Limitations -- 10 Future Scope -- References.; Review Rating Prediction Using Attention Bi-directional Gated Recurrent Unit with Domain Based Word Embedding -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Results Analysis -- 5 Conclusion -- References -- A Natural Way to Stability: A New Evolutionary Algorithm Based on Ocean Water Currents -- 1 Introduction -- 2 Literature Survey -- 3 Fundamental Concepts -- 3.1 Stability Point -- 3.2 Basic Mechanism of Ocean Water Currents-Based Optimization -- 4 Experimental Evaluation of OWCO on CEC Benchmark 2018 Competition Problems -- 4.1 CEC 2018 Results -- 4.2 Time Complexity -- 5 Conclusion -- References -- Emotion Recognition and Object Tracking Methodological Survey -- 1 Introduction -- 2 Object Detection and Tracking -- 3 Data Pre Processing -- 4 Feature Extraction -- 5 Kinect Sensors for Object Detection -- 6 Gesture and Emotion Recognition -- 7 Methodical Observations -- 7.1 Comparative Study and Data Analysis with a Profound Dataset -- 7.2 The Second Comparative Study Reveals About the Recognition of Emotions -- 7.3 By Usage of a Dataset of Images Captured Under Low-Light Conditions, Which May Include Poor Visibility, Noise, and Reduced Contrast. We Trained the Models to Detect and Recognize Objects or Emotions in These Images and Evaluate Their Performance ; Metrics -- 7.4 Conclusion of Comparative Analysis -- 8 Conclusion -- References -- Enhancing GNSS Positioning and Navigation Accuracy for Wireless Sensor Nodes -- 1 Introduction -- 1.1 Challenges and Issues -- 1.2 Motivation of the Research -- 1.3 Research Objectives -- 1.4 Contribution -- 1.5 Paper Organization -- 2 Background Details -- 2.1 Overview of GNSS System -- 2.2 Working Principle of GNSS System -- 2.3 Challenges in High-Precision GNSS-PN -- 2.4 Importance of Improving High-Precision GNSS-PN -- 3 Literature Review -- 4 Proposed Approach -- 4.1 Methodology.; 4.2 Data Collection (Step 1).
• Sommario/riassunto: This book is a collection of research papers presented at the International Conference on Intelligent Vision and Computing (ICIVC 2023), organized by the National Institute of Technology Agartala, India. It explores advancements in computational intelligence, focusing on topics such as machine learning, data science, robotics, and artificial intelligence. The book emphasizes adaptation, learning, and optimization in complex systems, offering insights into evolutionary computation, neural networks, and fuzzy systems. It serves as a reference for researchers and professionals interested in the latest developments in intelligent computing and its applications in solving real-world challenges. The proceedings aim to bridge the gap between academia and industry, fostering collaboration and innovation.