Recent Trends in AI Enabled Technologies : First International Conference, ThinkAI 2023, Hyderabad, India, December 29, 2023, Revised Selected Papers / edited by Gangamohan Paidi, Suryakanth V Gangashetty, Ashwini Kumar Varma.

Format:

Book

Contributor:

Paidi, Gangamohan, editor.

Gangashetty, Suryakanth V., editor.

Varma, Ashwini Kumar, editor.

Series:

Communications in Computer and Information Science, 1865-0937 ; 2045

Language:

English

Subjects (All):

Artificial intelligence.

Machine learning.

Image processing--Digital techniques.

Image processing.

Computer vision.

Artificial Intelligence.

Machine Learning.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Image Processing.

Computer Vision.

Local Subjects:

Artificial Intelligence.

Machine Learning.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Image Processing.

Computer Vision.

Physical Description:

1 online resource (100 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

This book constitutes the refereed proceedings of the First International Conference on Recent Trends in AI Enabled Technologies, ThinkAI 2023, which took place in Hyderabad, India, in December 2023. The 7 full papers presented in these proceedings were carefully reviewed and selected from 51 submissions. The conference focuses on on up to date topics and recent trends in artificial intelligence and related technologies. .

Contents:

Intro

Preface

Organization

Contents

A Simple Machine Unlearning Approach Using Elastic Weight Consolidation

1 Introduction

2 A Machine Unlearning Approach Using Elastic Weight Consolidation

2.1 Elastic Weight Consolidation

2.2 Machine Unlearning Through Continual Learning

3 Performance Evaluation

3.1 Dataset

3.2 Network Architecture

3.3 Metrics

3.4 Experimental Results

4 Conclusion and Future Work

References

On the Road to Autonomy: A Comparative Analysis of Multimodal Datasets

2 Dataset Analysis

2.1 KITTI

2.2 NuScenes

2.3 Cityscapes

2.4 Oxford Robotcar Dataset

2.5 Waymo

2.6 IDD: Indian Driving Dataset

3 Research Gap

Real-Time Duration Modification Using Frame Level Epoch Extraction

2 Real-Time Duration Modification

Revolutionizing COVID-19 Patient Identification: Multi-modal Data Analysis with Emphasis on CNN Algorithm

1.1 The Critical Need to Identify COVID-19 Cases

1.2 Multi-modal Data Analysis's Function

1.3 Automated Applications' Significance

1.4 Worldwide COVID-19 Pandemic Data

2 Literature Survey

3 Methodology

3.1 Data Collection

3.2 Data Preprocessing

3.3 Data Augmentation

3.4 Feature Extraction

3.5 Model Selection

3.6 Model Training

3.7 Model Evaluation

3.8 Model Deployment

3.9 Overall Flowchart

3.10 Data Allocation

4 Results

5 Conclusion

Compact SVD Based Representation of CNN Kernels for Classification and Time Complexity Analysis

2 Low-Rank Approximation of CNN Kernels Using Compact SVD for Time Complexity Analysis of Spatial Filtering

2.1 Low-Rank Approximation of a Matrix Using Compact SVD

2.2 Time Complexity and Separability of Two Dimensional Spatial Filters Used in CNN.

2.3 Compact SVD Based Representation of CNN Kernels

3 Performance Analysis

3.1 Model Architecture and Dataset

3.2 Test Accuracy and Time Complexity Analysis

4 Conclusions

A Block-Wise SVD Approach for Simultaneous ROI Preservation, Background Blurring, and Image Compression

2 Literature Review

2.1 SVD in Image Processing

2.2 Deep Learning in Object Detection

3 Integration of SVD in Object Detection and Image Compression

3.1 Key Metrics for Evaluation

3.2 Research Gaps and Contributions

4 Methodology

4.1 Model Selection and Integration: YOLOv8 by Ultralytics

4.2 YOLO Model Architecture

4.3 Object Detection Process

4.4 Target Class Filtering

4.5 Block Selection and Application of SVD

4.6 Minimum Bounding Box Calculation

4.7 SVD Rank and Image Transformation

4.8 Block-Wise Image Modification

4.9 Clipping and Preservation of Pixel Values

5 Exerimental Results

5.1 Using YOLOv8 to Identify the Region of Interest

5.2 Applying Block-SVD

6 Observations

7 Conclusion

Continuous Integration, Delivery and Deployment: A Systematic Review of Approaches, Tools, Challenges and Practices

3.1 Research Design

3.2 Data Collection

3.3 Semi-structured Interviews

3.4 Sampling

3.5 Data Analysis

4.1 Prevalence of CI/CD Adoption

5 Limitations

5.1 Cultural Bias

5.2 Sampling Bias

5.3 Self-reporting Bias

5.4 Dynamic Nature of Technology

5.5 Limited Industry Scope

6 Discussion

6.1 The Widespread Adoption of CI/CD

6.2 Impact on Software Development Processes

6.3 Implication

6.4 Perceived Benefits and Challenges

6.5 Implication

6.6 Efficiency and Competitiveness of the Organization

6.7 Current Trends and Future Directions:.

6.8 Shift Left Testing

6.9 Infrastructure as Code (IaC)

6.10 Containerization and Orchestration

6.11 Micro services Architecture

6.12 Scalability and Future Considerations

6.13 Implication

6.14 Broader Industry Trends

6.15 Implication

Author Index.

Notes:

Includes bibliographical references and index.

ISBN:

9783031591143

3031591143