Intro
Organization
Preface
Contents
Artificial Intelligence for Multimedia Processing
Low 3D-HEVC Depth Map Intra Modes Selection Complexity Based on Clustering Algorithm and an Efficient Edge Detection
1 Introduction
2 Structure Tensors and AM-PCM Algorithm with the Features Selections
2.1 Structure Tensors
2.2 AM-PCM Algorithm with the Features Selections
3 Proposal Intra-Decision Model
4 Experimental Results
5 Conclusion
References
Longitudinal Study of the Thyroid Surgery Effect Based on Computer Vision
1 Introduction
2 Dataset Preparation

2.1 Acquisition
2.2 Determining the Cycles
2.3 Delimitation of Regions of Interest
3 Feature Extraction
3.1 Salient Informations
3.2 Definition of the Descriptors
3.3 Set of Features
4 Statistical Analysis
4.1 Motivation
4.2 Principle of the Univariate ANOVA Test
4.3 Experimental Results of the ANOVA Test
4.4 Multivariate Statistical Test
4.5 Experimental Results with Automatic Segmentation
5 Conclusion
References
Pectoral Muscle Segmentation Using Mammogram Images in Medio Lateral Oblique View
1 Introduction
2 Background

3 The Proposed Approach
3.1 Preprocessing
3.2 Segmentation
4 Experiments and Discussion
4.1 Evaluation Metrics
5 Conclusion
References
A Nearest Neighbor-Based Hamiltonian Clustering Algorithm
1 Introduction
2 Related Works
3 Proposed Method
3.1 Computing the Nearest Neighbor Hamiltonian Path
3.2 Finding the Clusters
3.3 Assembling Clusters
4 Experiments and Comparative Results
5 Conclusion
References
An Acoustic Analysis of Voice Before and After Thyroidectomy
1 Introduction
1.1 Background
2 Methodology
3 Materials

3.1 Features Extraction
4 Results
4.1 Discrimination Abilities
5 Discussion
6 Conclusion
References
Estimation of Water Turbidity by Image-Based Learning Approaches
1 Introduction
2 Database Production
2.1 Sampled Image Acquisition
2.2 Data Preparation
2.3 Producing the Annotated Dataset
3 Conventional Machine Learning Methods
3.1 Motivations
3.2 Textural Features
3.3 Color Features
3.4 Classification
4 Deep Learning Methods
4.1 Proposed Architectures
4.2 Data Augmentation
5 Experimental Results

5.1 Selection of the Best Combination of Handcrafted Features
5.2 Performances of Machine Learning Methods
5.3 Performance of the DL Approaches
5.4 Comparison Between ML and DL Approaches
6 Conclusion
References
An Image Compression Approach Based on Convolutional AutoEncoder
1 Introduction
2 State of the Art
3 Methods
3.1 The Proposed Compression Network
3.2 Baseline Network
4 Experiment Results
5 Conclusion
References
Offline Writer Identification Based on Diagonal Gradient Angle of Small Fragments
1 Introduction
2 Methodology