Linked e-resources
Details
Table of Contents
Preface; Organizing Committee; General Chairs; Steering Committee; Program Chair; Publicity Chairs; Financial Chair; Publication Chairs; Organizers and Supporters; Program Committee; Contents; Machine Learning and Deep Learning; Image-Based Content Retrieval via Class-Based Histogram Comparisons; Abstract; 1 Introduction; 2 Research in Image-Based Recall; 3 IBR Packages; 4 Experimental Setup and Methodology; 5 Results; 6 Conclusions and Future Work; References; Smart Content Recognition from Images Using a Mixture of Convolutional Neural Networks; Abstract; 1 Introduction; 2 Related Works
3 The Proposed Mixture of CNN Model4 Dataset; 5 Experimental Results; 6 Conclusion; References; Failure Part Mining Using an Association Rules Mining by FP-Growth and Apriori Algorithms: Case of ATM Maintenance in Thailand; Abstract; 1 Introduction; 2 Relate Work; 2.1 Association Rules; 2.2 Apriori; 2.3 FP-Growth; 3 The Proposed Model; 4 Result and Discussion; 5 Conclusion; Acknowledgements; References; Improving Classification of Imbalanced Student Dataset Using Ensemble Method of Voting, Bagging, and ...; Abstract; 1 Introduction; 2 Methodology and Related Work; 2.1 Resampling
2.2 Feature Selection2.3 Ensemble; 2.4 Classifier; 2.5 Evaluation; 3 The Proposed Method; 3.1 Student Data; 3.2 Data Preprocessing; 4 Experiment and Result; 5 Conclusion; Acknowledgements; References; Reduction of Overfitting in Diabetes Prediction Using Deep Learning Neural Network; Abstract; 1 Introduction; 2 Proposed Method; 2.1 Multilayer Perceptron; 2.2 Dropout; 3 Experimental Results and Analysis; 4 Conclusion; Acknowledgements; References; An Improved SVM-T-RFE Based on Intensity-Dependent Normalization for Feature Selection in Gene Expre ...; Abstract; 1 Introduction
2 Materials and Methods2.1 Data; 2.2 SVM-RFE Algorithm; 2.3 Feature Ranking Algorithms for Gene Selection; 2.4 MA-Plot-Based Methods for Normalization; 3 The Proposed Algorithm; 4 The Proposed Algorithm Evaluation; 5 Conclusion; References; Vehicle Counting System Based on Vehicle Type Classification Using Deep Learning Method; Abstract; 1 Introduction; 2 Methodology; 2.1 Vehicle Counting System (VCS); 2.2 Vehicle Type Classification
CNNLS; 3 Result and Discussion; 4 Conclusion; References; Metadata Discovery of Heterogeneous Biomedical Datasets Using Token-Based Features; Abstract
1 Introduction2 Methods; 2.1 Data Sources and Types; 2.2 Token-Based Features; 2.3 Decision Tree Models Building and Evaluation; 3 Results; 4 Discussion; 5 Conclusion; Acknowledgments; References; Heavy Rainfall Forecasting Model Using Artificial Neural Network for Flood Prone Area; Abstract; 1 Introduction; 2 Materials and Methods; 2.1 Study Area; 2.2 Handling Missing Data; 2.3 Data Gathering; 2.4 Data Normalization; 2.5 Development of Artificial Neural Networks (ANN); 3 Results and Discussion; 4 Conclusion; References; Communication and Signal Processing
3 The Proposed Mixture of CNN Model4 Dataset; 5 Experimental Results; 6 Conclusion; References; Failure Part Mining Using an Association Rules Mining by FP-Growth and Apriori Algorithms: Case of ATM Maintenance in Thailand; Abstract; 1 Introduction; 2 Relate Work; 2.1 Association Rules; 2.2 Apriori; 2.3 FP-Growth; 3 The Proposed Model; 4 Result and Discussion; 5 Conclusion; Acknowledgements; References; Improving Classification of Imbalanced Student Dataset Using Ensemble Method of Voting, Bagging, and ...; Abstract; 1 Introduction; 2 Methodology and Related Work; 2.1 Resampling
2.2 Feature Selection2.3 Ensemble; 2.4 Classifier; 2.5 Evaluation; 3 The Proposed Method; 3.1 Student Data; 3.2 Data Preprocessing; 4 Experiment and Result; 5 Conclusion; Acknowledgements; References; Reduction of Overfitting in Diabetes Prediction Using Deep Learning Neural Network; Abstract; 1 Introduction; 2 Proposed Method; 2.1 Multilayer Perceptron; 2.2 Dropout; 3 Experimental Results and Analysis; 4 Conclusion; Acknowledgements; References; An Improved SVM-T-RFE Based on Intensity-Dependent Normalization for Feature Selection in Gene Expre ...; Abstract; 1 Introduction
2 Materials and Methods2.1 Data; 2.2 SVM-RFE Algorithm; 2.3 Feature Ranking Algorithms for Gene Selection; 2.4 MA-Plot-Based Methods for Normalization; 3 The Proposed Algorithm; 4 The Proposed Algorithm Evaluation; 5 Conclusion; References; Vehicle Counting System Based on Vehicle Type Classification Using Deep Learning Method; Abstract; 1 Introduction; 2 Methodology; 2.1 Vehicle Counting System (VCS); 2.2 Vehicle Type Classification
CNNLS; 3 Result and Discussion; 4 Conclusion; References; Metadata Discovery of Heterogeneous Biomedical Datasets Using Token-Based Features; Abstract
1 Introduction2 Methods; 2.1 Data Sources and Types; 2.2 Token-Based Features; 2.3 Decision Tree Models Building and Evaluation; 3 Results; 4 Discussion; 5 Conclusion; Acknowledgments; References; Heavy Rainfall Forecasting Model Using Artificial Neural Network for Flood Prone Area; Abstract; 1 Introduction; 2 Materials and Methods; 2.1 Study Area; 2.2 Handling Missing Data; 2.3 Data Gathering; 2.4 Data Normalization; 2.5 Development of Artificial Neural Networks (ANN); 3 Results and Discussion; 4 Conclusion; References; Communication and Signal Processing