Key Digital Trends in Artificial Intelligence and Robotics. Proceedings of 4th International Conference on Deep Learning, Artificial Intelligence and Robotics, (ICDLAIR) 2022 - Progress in Algorithms and Applications of Deep Learning

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Preface Organization Contents A Study Review of Neural Audio Speech Transposition over Language Processing 1 Introduction 2 Brief Background 3 Methodology 3.1 Statistical Approach 3.2 Experimental Setup and Evaluation Protocol 3.3 CNN Model 3.4 LSTM 3.5 Attention Mechanism 3.6 Findings and Limitation 4 Impact of Result 5 Conclusion References DCNN Based Disease Prediction of Lychee Tree 1 Introduction 2 Literature Review 3 Proposed Methodology 3.1 Dataset 3.2 Data Pre-processing 3.3 Model Evaluation 3.4 InceptionV3 3.5 VGG16 3.6 MobileNet 3.7 NASNetMobile 3.8 Parameter Setting 4 Result and Discussion 5 Conclusion References MEVSS: Modulo Encryption Based Visual Secret Sharing Scheme for Securing Visual Content 1 Introduction 2 Related Work 3 Proposed Algorithm 4 Performance Analysis 5 Results and Discussion 6 Conclusion References Analysis of Bangla Transformation of Sentences Using Machine Learning 1 Introduction 2 Literature Review 2.1 Comparison 3 Methodology 3.1 Dataset Preparation 3.2 Data Collection 3.3 Preprocessing of Data 3.4 Data Vectorization or Distribution 4 Model and Performance 4.1 Proposed Model 4.2 Model Performance 5 Result and Discussion 6 Conclusion References Towards a Novel Machine Learning and Hybrid Questionnaire Based Approach for Early Autism Detection 1 Introduction 2 Related Works 3 Hybridisation Approach 4 Experimental Setup 4.1 Hybrid Questionnaire 4.2 Data Collection 4.3 Models Testing and Results 5 Discussion and Evaluation 6 Conclusion and Perspectives References Bi-RNN and Bi-LSTM Based Text Classification for Amazon Reviews 1 Introduction 2 Related Work 3 Proposed Model 3.1 Bi-RNN Model for the Amazon Review Binary Classification 3.2 Bi-LSTM Model for the Amazon Review Binary Classification 4 Result Analysis 4.1 Dataset 4.2 Training/Testing Procedure 4.3 Results 5 Conclusion References Resource Utilization Tracking for Fine-Tuning Based Event Detection and Summarization Over Cloud 1 Introduction 2 Related Work 3 Proposed Approach 3.1 Virtual Machine Scheduling Using OpenStack Cloud 3.2 YOLOv5 Based Model Training and Fine Tuning 4 Results and Discussion 4.1 Comparison with Related Works 5 Conclusion References Automatic Fake News Detection: A Review Article on State of the Art 1 Introduction 2 Existing Works 2.1 Evaluation Metrics 2.2 Content-Based Fake News Detection 2.3 Context-Based Fake News Detection 2.4 Hybrid Fake News Detection 3 Datasets 4 Discussion 5 Conclusion References Cascaded 3D V-Net for Fully Automatic Segmentation and Classification of Brain Tumor Using Multi-channel MRI Brain Images 1 Introduction 1.1 Contributions of This Work 2 Related Work 3 Proposed Methodology 3.1 Data Collection and Preprocessing 3.2 Segmentation and Feature Extraction 3.3 Proposed Model Creation 3.4 Performance Assessment and Comparison 4 Results and Discussion 5 Conclusion References Computing Physical Stress During Working Shift with Deep Neural Networks 1 Introduction 2 Methodology 2.1 3D Human Pose Estimation 2.2 Worker Posture Metrics Computation 2.3 RULA Risk Index Computing 3 Experimental Setup 4 Experimental Evidence 5 Conclusion and Future Directions References Trend Prediction in Finance Based on Deep Learning Feature Reduction 1 Introduction 2 Preliminaries 2.1 Restricted Boltzmann Machine 2.2 Auto-Encoders 3 Experimental Results 3.1 Input Features and Data Labeling 3.2 Experiment Setting 3.3 Model Fitting 3.4 Performance Results 3.5 AE vs. RBM 4 Conclusions and Future Works References A Preliminary Study on AI for Telemetry Data Compression 1 Introduction 2 Related Work 3 Materials and Methods 4 Experimental Results 5 Discussion 6 Conclusions References On the Use of Multivariate Medians for Nearest Neighbour Imputation 1 Introduction 2 Preliminaries on Multivariate Medians 3 Robust Multivariate Imputation 4 Experiments on Artificially Generated Data 5 Conclusions References Decision Making by Applying Machine Learning Techniques to Mitigate Spam SMS Attacks 1 Introduction 2 Related Work 2.1 Background 2.2 Usage of Machine Learning Techniques for Decision-Making 2.3 Applied Machine Learning Algorithms 2.4 Utilising Machine Learning Techniques to Mitigate Spams 3 Methodology 3.1 The Delphi Decision-Making Study Method 3.2 Software Development Methodology and Algorithms 3.3 Data Collection and Processing 3.4 Experimental Study and Implementation 4 Discussions and Findings 4.1 Delphi’s Reliability and Validity for Decision-Making 4.2 Clustering Based Classification for Decision-Making to Mitigate Spam 5 Conclusion References Voronoi Diagram-Based Approach to Identify Maritime Corridors 1 Introduction 2 Problem Description 3 Corridors Generation Procedure 3.1 Spatial Data Transformation 3.2 Construction of the Connectivity Graph 3.3 Identification of Corridors 4 Application and Results 5 Conclusion and Future Work References Author Index