New approaches for multidimensional signal processing [electronic resource] : proceedings of International Workshop, NAMSP 2020 / Roumen Kountchev, Rumen Mironov, Shengqing Li, editors.
This book is a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2020), held at Technical University of Sofia, Sofia, Bulgaria, during 0911 July 2020. The book covers research papers in the field of N-dimensional multicompone...
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Full Text (via Springer) |
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| Corporate Author: | |
| Other Authors: | , , |
| Other title: | NAMSP 2020. |
| Format: | Electronic Conference Proceeding eBook |
| Language: | English |
| Published: |
Singapore :
Springer,
2021.
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| Series: | Smart innovation, systems, and technologies ;
216. |
| Subjects: |
MARC
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| 245 | 1 | 0 | |a New approaches for multidimensional signal processing |h [electronic resource] : |b proceedings of International Workshop, NAMSP 2020 / |c Roumen Kountchev, Rumen Mironov, Shengqing Li, editors. |
| 246 | 3 | |a NAMSP 2020. | |
| 260 | |a Singapore : |b Springer, |c 2021. | ||
| 300 | |a 1 online resource (271 pages) | ||
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| 490 | 1 | |a Smart Innovation, Systems and Technologies ; |v v.216. | |
| 500 | |a "This book presents the result of the International Workshop "New Approaches forMultidimensional Signal Processing--NAMSP 2020" which was carried out online,during July 9-11, 2020, at the Technical University of Sofia, Bulgaria." | ||
| 505 | 0 | |a Intro -- International Program Committee -- Preface -- Contents -- About the Editors -- 1 Computational Intelligence for Brain Tumors Detection -- 1.1 Introduction -- 1.2 Computational Intelligence Paradigms -- 1.3 Computational Intelligence Applications in Intelligent Health Informatics -- 1.4 Deep Learning Paradigm in Health Informatics -- 1.5 Medical Imaging Techniques for Human Brain -- 1.5.1 Medical Aspects -- 1.5.2 Magnetic Resonance Imaging (MRI) -- 1.5.3 General Methodology of Brain Images Processing -- 1.5.4 CI Techniques for Segmentation and Classification Processes. | |
| 505 | 8 | |a 1.6 Brain Tumor Diagnosis Using CI Techniques -- 1.6.1 1st Application: Developing CAD Systems for Brain Tumor Diagnosis -- 1.6.2 2nd Application: Classification Using Deep Learning for Brain Tumors -- 1.7 Recommendations and Conclusions -- 1.7.1 Recommendation -- 1.8 Conclusions -- References -- 2 Video-Based Monitoring and Analytics of Human Gait for Companion Robot -- 2.1 Introduction -- 2.2 Related Work -- 2.3 Methodology -- 2.3.1 Pipeline Overview -- 2.3.2 Pose Estimation and Skeleton Extraction -- 2.3.3 Gait and Postural Feature Extraction -- 2.3.4 Time Series Analysis. | |
| 505 | 8 | |a 2.4 Experiments and Results -- 2.4.1 Data Collection -- 2.4.2 Experiment Setting -- 2.4.3 Results for Gait Classification -- 2.4.4 Discussion -- 2.4.5 Graphical User Interface and Companion Robot -- 2.5 Conclusions and Future Work -- References -- 3 Comparative Analysis of the Hierarchical 3D-SVD and Reduced Inverse Tensor Pyramid in Regard to Famous 3D Orthogonal Transforms -- 3.1 Introduction -- 3.2 Tensor Decomposition Through 3D Truncated Hierarchical SVD -- 3.2.1 Decomposition of Elementary Tensor of Size 2 × 2 × 2 Through 3D Truncated Hierarchical SVD. | |
| 505 | 8 | |a 3.2.2 Decomposition of a Tensor of Size N × N × N Through 3D Truncated Hierarchical SVD -- 3.2.3 Calculation of 3D-THSVD for Third-Order Tensor of Size N × N × N -- 3.3 Tensor Decomposition Based on the 3D Reduced Inverse Spectrum Pyramid -- 3.4 Comparison of the CC of the Famous Deterministic and Statistical Hierarchical 3D Decompositions -- 3.4.1 CC of the Deterministic Hierarchical 3D Decompositions: RISP, SDT, FFT and DWT -- 3.4.2 CC of the Statistical Hierarchical 3D Decompositions HSVD, THSVD, and H-Tucker -- 3.4.3 Comparison Evaluation of the CC for the Analyzed 3D Decompositions. | |
| 505 | 8 | |a 3.5 Conclusions -- References -- 4 Tracking of Domestic Animals in Thermal Videos by Tensor Decompositions -- 4.1 Introduction -- 4.2 Evaluated Algorithms -- 4.2.1 Tucker-ALS -- 4.2.2 Tucker-ADAL -- 4.2.3 CP-ALS -- 4.2.4 HoRPCA-S -- 4.2.5 Score Fusion -- 4.3 Experimental Results -- 4.4 Discussion -- 4.5 Conclusion -- References -- 5 Partial Contour Matching Based on Affine Curvature Scale Space Descriptors -- 5.1 Introduction -- 5.2 Affine Curvature Scale Space Curve Matching Algorithm -- 5.2.1 Affine Curvature Scale Space Descriptor (ACSS) -- 5.2.2 Affine Curve Matching (ACM) Algorithm. | |
| 500 | |a 5.3 Experiments. | ||
| 500 | |a Includes author index. | ||
| 520 | |a This book is a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2020), held at Technical University of Sofia, Sofia, Bulgaria, during 0911 July 2020. The book covers research papers in the field of N-dimensional multicomponent image processing, multidimensional image representation and super-resolution, 3D image processing and reconstruction, MD computer vision systems, multidimensional multimedia systems, neural networks for MD image processing, data-based MD image retrieval and knowledge data mining, watermarking, hiding and encryption of MD images, MD image processing in robot systems, tensor-based data processing, 3D and multi-view visualization, forensic analysis systems for MD images and many more. | ||
| 588 | 0 | |a Online resource; title from PDF title page (SpringerLink, viewed April 6, 2021) | |
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| 655 | 7 | |a Conference papers and proceedings. |2 fast |0 (OCoLC)fst01423772. | |
| 700 | 1 | |a Kountchev, Roumen. |0 http://id.loc.gov/authorities/names/no2012063450 |1 http://isni.org/isni/000000036696012X. | |
| 700 | 1 | |a Mironov, Rumen. | |
| 700 | 1 | |a Li, Shengqing. | |
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| 830 | 0 | |a Smart innovation, systems, and technologies ; |v 216. |0 http://id.loc.gov/authorities/names/no2010151051. | |
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