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Advances in Information and Communication : Proceedings of the 2019 Future of Information and Communication Conference (FICC). Volume 2.

Author: Kohei Arai; Rahul Bhatia
Publisher: Cham : Springer, ©2020.
Series: Lecture notes in networks and systems, v. 70.
Edition/Format:   eBook : Document : Conference publication : EnglishView all editions and formats
Summary:
This book presents a remarkable collection of chapters that cover a wide range of topics in the areas of information and communication technologies and their real-world applications. It gathers the Proceedings of the Future of Information and Communication Conference 2019 (FICC 2019), held in San Francisco, USA from March 14 to 15, 2019. The conference attracted a total of 462 submissions from pioneering  Read more...
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Genre/Form: Electronic books
Conference papers and proceedings
Congresses
Additional Physical Format: Print version:
Arai, Kohei.
Advances in Information and Communication : Proceedings of the 2019 Future of Information and Communication Conference (FICC), Volume 2.
Cham : Springer, ©2019
Material Type: Conference publication, Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Kohei Arai; Rahul Bhatia
ISBN: 9783030123857 3030123855
OCLC Number: 1085169065
Notes: A Two-Fold Machine Learning Approach for Efficient Day-Ahead Load Prediction at Hourly Granularity for NYC
Description: 1 online resource (1269 pages)
Contents: Intro; Preface; Contents; Contextual Binding: A Deductive Apparatus in Artificial Neural Networks; Abstract; 1 Introduction; 1.1 A Subsection Sample; 2 Issues; 2.1 Incompleteness of Input Datasets; 2.2 Inaccuracy of Output; 2.3 Issue Within the Hidden Layers; 3 Proposal; 4 Discussion; 4.1 Advantages of the New Approach; 4.2 Implementation; 5 Conclusion; References; Intelligent Signal Classifier for Brain Epileptic EEG Based on Decision Tree, Multilayer Perceptron and Over-Sampling Approach; Abstract; 1 Introduction; 1.1 What Is Epilepsy; 1.2 Diagnosis and Treatment 1.3 Electroencephalogram (EEG)1.4 Imbalanced Data; 1.5 Research Process; 2 Materials and Methods; 2.1 Source; 2.2 Fast Fourier Transform; 2.3 Data Preprocessing; 2.4 Decision Tree; 2.5 Multiple Layer Perceptron; 3 Experiments and Results; 3.1 Research Process; 3.2 Signal Processing and Feature Extraction; 3.3 Result of Data Preprocessing; 3.4 Construction of Classification; 3.5 Evaluation of Classification Model; 4 Conclusion; Acknowledgements; References; Korean-Optimized Word Representations for Out-of-Vocabulary Problems Caused by Misspelling Using Sub-character Information; Abstract 1 Introduction2 Related Works; 3 Methods; 3.1 Jamo-Static Model; 3.2 Jamo-Advanced Model for Misspelling; 4 Experimental Setup; 4.1 A Model Variations; 4.2 Datasets; 4.3 Implementation Details; 5 Results; 5.1 Correlation with Human Judgment; 5.2 Similarity Between Misspelled Words and Corrected Words; 6 Conclusions and Further Works; Acknowledgements; References; A Regressive Convolution Neural Network and Support Vector Regression Model for Electricity Consumption Forecasting; 1 Introduction; 2 Methodologies; 2.1 Data Prepossessing; 2.2 RCNN Architecture; 2.3 SVR; 2.4 RCNN-SVR; 3 Results 3.1 Evaluation of Model Accuracy3.2 Forecasting of Electricity Consumption of Each Month in 2018; 4 Discussion; 5 Conclusions; References; Facial Expression Recognition and Analysis of Interclass False Positives Using CNN; 1 Introduction; 2 Related Work; 3 Proposed Deep Learning Model; 4 Experiments and Results; 5 Conclusion; References; CASCADENET: An LSTM Based Deep Learning Model for Automated ICD-10 Coding; 1 Introduction; 2 Related Work; 3 Background; 3.1 ICD-10 Coding System; 3.2 Clinical Documents Versus Diagnosis Phrases; 3.3 Q-Map; 3.4 Negation Detection; 4 Optimization Objectives 4.1 One-Step Classification4.2 Hierarchical Classification; 5 Architecture and Procedure; 5.1 Training Data; 5.2 Word Embeddings; 5.3 Preprocessing; 5.4 Experiments; 5.5 LSTM Architecture and Training; 6 Results and Discussion; 7 Conclusion; References; Automated Gland Segmentation Leading to Cancer Detection for Colorectal Biopsy Images; Abstract; 1 Introduction; 2 Methodology; 2.1 Image Acquisition; 2.2 Preprocessing; 2.3 Image Segmentation; 2.4 Classification; 3 Result and Discussion; 4 Conclusion; Acknowledgements; References
Series Title: Lecture notes in networks and systems, v. 70.
Other Titles: FICC 2019

Abstract:

This book presents a remarkable collection of chapters that cover a wide range of topics in the areas of information and communication technologies and their real-world applications.  Read more...

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