Data Engineering and Applications Proceedings of the International Conference, IDEA 2K22, Volume 2 /
| Corporate Author: | |
|---|---|
| Other Authors: | , , , |
| Summary: | X, 471 p. 187 illus., 152 illus. in color. text |
| Language: | English |
| Published: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2024.
|
| Edition: | 1st ed. 2024. |
| Series: | Lecture Notes in Electrical Engineering,
1189 |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-981-97-2451-2 |
| Format: | Electronic Book |
Table of Contents:
- Review of Methods for Handling Class-Imbalanced in Classification Problems
- Course Material Recommendation System Using Student Learning Behavior and Course Material Complexity Score for Slow Learner Students
- A Benchmarking Investigation of Evolutionary Algorithms to resolve the COVID Sample Collection Problem
- Using OpenNLP and GraalVM to detect sentences in Kubernetes while comparing Helidon and Spring Boot's metrics
- An Efficient Hybrid Model to Summarize the Text using Transfer Learning
- Automatic Detection of Learner's Learning Style
- Construction of an Intelligent Knowledge based System using Transformer Model
- Machine Learning-Based Disease Diagnosis using Body Signals: A Review
- Finite-Difference and Finite-Volume 1D Steady-State Heat Conduction model for Machine Learning Algorithms
- Sign Language Detection Through PCANet and SVM
- A Novel Surface Roughness Estimation and Optimization Model for Turning Process Using RSM-JAYA Method
- Effective Prediction of Coronary Heart Disease Using Hybrid Machine Learning
- Feature Extraction Using Levy Distribution-Based Salp Swarm Algorithm
- Plant Disease Detection using Machine Learning Approaches: A Review
- Copy Move Forgery Detection Algorithm: A Machine Learning based approach to detect Image Forgery
- A Machine Learning based Approach to Combat Hate Speech on Social Media
- Prediction of SARS – COVID – 19 Based on Transfer Machine Learning Techniques using Lungs CT Scan Images
- Online Document Identification and Verification using Machine Learning Model.