Intro
Preface
Contents
Editors and Contributors
Optimization of Accuracy of Tweets for Coronavirus Pandemic Using BERT-Based CNN Model
1 Introduction
2 Related Work
3 CNN
4 Proposed Methodology
5 Simulation Result
6 Conclusion and Future Work
References
Deep Learning Neural Networks for Forecasting the Abrasive Wear in Machining Tools for Cryogenic Treatment by Process Parameter Optimization
1 Introduction
1.1 Motivation of This Work
1.2 Objectives of This Work
2 Literature Survey
3 Materials and Methods
3.1 Black Widow Optimization

3.2 Methodology
4 Results and Discussion
4.1 Data Collection
4.2 Results for Conventional ANN and Deep Learning-Based Hybrid Neural Networks for Abrasive Wear Monitoring in Cryogenic Treatment
4.3 The Architecture of Healthcare IoT
5 Conclusion
References
Real-Time Indian Sign Language Detection
1 Introduction
2 Literature Review
2.1 Existing System
2.2 Proposed System
3 System Design and Architecture
3.1 Users of System
3.2 System Architecture
3.3 Tool Used
4 Methodology
4.1 Data Acquisition
4.2 Data Labeling
4.3 Hand Detection

4.4 Segmentation and Preprocessing
4.5 Text Interpretation
5 Result
6 Advantages
7 Limitation
8 Future Scope
9 Conclusion
References
Deep Learning-Based Lung Cancer Detection and Classification
1 Introduction
2 Literature Survey
3 Proposed Architecture and Methodology
3.1 Proposed Architecture
3.2 Proposed Methodology
4 Experimental Investigations
4.1 Dataset
4.2 Discussion on Results
5 Conclusion
References
Improved Deep Learning Approach for Underwater Image Enhancement
1 Introduction
1.1 Literature Review

2 Fast Underwater Image Enhancement GAN
2.1 The Generator
2.2 The Discriminator
3 Improved Fast Underwater Image Enhancement GAN Architecture
3.1 Dataset
3.2 Network Architecture
3.3 Loss Functions
4 Results and Discussion
4.1 Quantitative Evaluation
4.2 Qualitative Evaluation
5 Conclusion and Future Work
References
Machine Learning-Based Autonomous Framework for Product Classification Over Cloud
1 Introduction
2 Literature Review
2.1 Review of Machine Learning Approaches
2.2 Relevant Researches in the E-commerce Classification Field

3 Proposed Work
4 Experiment and Result Analysis
4.1 Microsoft Azure ML Workspace [16]
4.2 Dataset Description and Simulation Parameters
4.3 Experiment
4.4 Performance Parameters
4.5 Result Analysis
5 Conclusion and Future Scope
References
Automatic Traffic Rule Violations Detection Using Deep Learning Techniques
1 Introduction
2 Related Work
3 Proposed Technique
3.1 Processing of Images
3.2 YOLOv5
3.3 OpenALPR API
3.4 Twilio Messenger
4 Methodology
5 Results
6 Conclusion
References