Intro
Preface
Organization
Contents
Part II
Contents
Part I
Machine Learning
Deep Learning Based Automated Vickers Hardness Measurement
1 Introduction and Related Work
2 Methodology
2.1 Indentation Segmentation Using Convolutional Neural Network
2.2 Edge Extraction and Initial Indention Vertex Position Estimation
2.3 Precision Improvement
3 Experimental Framework
4 Experiments and Results
5 Conclusion
References
ElasticHash: Semantic Image Similarity Search by Deep Hashing with Elasticsearch
1 Introduction
2 Related Work

3 ElasticHash
3.1 Deep Hashing Model
3.2 Integration into ES
4 Experimental Evaluation
4.1 Results
5 Conclusion
References
Land Use Change Detection Using Deep Siamese Neural Networks and Weakly Supervised Learning
1 Introduction
2 Related Work
3 Methodology
3.1 Multi Filter Multi-scale Deep Convolutional Neural Network
3.2 Siamese Neural Network
3.3 Generation of Change Detection Maps
4 Experimental Setup
4.1 Datasets' Description
4.2 Model Adaptation and Parameter Setting
5 Results
5.1 Ablation Analysis of the Proposed Model
6 Conclusions

5.3 Results
6 Conclusions
References
Unsupervised Recognition of the Logical Structure of Business Documents Based on Spatial Relationships
1 Introduction and Context
2 State of the Art
3 Proposal
4 Spatial Contexts
4.1 Metadata to Captions Spatial Context (MCSC)
4.2 Metadata to Metadata Spatial Context (MMSC)
5 Voting and Detection Stages
5.1 Voting by Using Metadata Position
5.2 Voting by Using the Metadata to Captions Spatial Context
5.3 Voting by Using the Metadata Format
5.4 Voting by Using the MMSC
5.5 Detection Stage
6 Results
7 Conclusion