New Approaches for Multidimensional Signal Processing
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New Approaches for Multidimensional Signal Processing

New Approaches for Multidimensional Signal Processing


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About the Book

This book is a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2025), held at Technical University of Sofia, Sofia, Bulgaria, during July 24–26, 2025. The book covers research papers in the field of N-dimensional multicomponent image processing, multidimensional (MD) image representation and super-resolution, 3D image processing and reconstruction, MD computer vision systems, MD multimedia systems, data-based MD image retrieval and knowledge data mining, jamming image recognition and surface defects segmentation, MD signal analysis aimed at medical decision support, MD image processing in robot systems, 3D and multi-view visualization in environmental art, VR and reinforcement learning applications, tensor-based mip-map implementation, recursive filtration of MD images, and many more.



Table of Contents:

Tensor Elastic Net (T-NET) for Robust Solutions to Sparse Multilinear Least Squares Problems.- Exploring the Optimizing Tools for Digital Watermark-ing of Medical Visual Information using DL.- Intelligent Decision on Stroke Biomarkers: Potentials and Constraints.- Optimizing Dilated SE-DenseNet for Brain Tumor MRI Classification: A Targeted Approach within the Broader Landscape of Computer-Aided Diagnosis.- Wavelet-Based Image Fusion of Pre-Registered MRI and PSMA Scans of the Prostate Gland.- Unsupervised Signal Decomposition and Tracking using Hyperdimensional Computing and Spiking Neural Networks.- An In-Depth Review of Routing Protocols in IoT-Oriented Sensor Networks.- Automated Identification of Vascular Plaque in Optical Coherence Tomography Images.- Construction of a Quantitative Analysis and Prediction Model for the Antioxidant Effects of Polysaccharides from Polygonatum sibiricum and Lycium barbarum Based on Machine Learning.- Neuromorphic Directional Motion Detector.- Correlation Analysis Between Regional Economic Development and Policy Combined with Machine Learning.- Quantifying and Forecasting the Impact of Employment Structure Preferences on the Digital Economy: A Machine Learning-Augmented Panel Data Analysis.- Trade Network Analysis and Economic Stability Forecasting Using Graph Attention Networks.- Multi-source Heterogeneous Data Fusion and Intelligent Decision Algorithm Design for Cross-border Trade.- AI-Driven Optimization of Enterprise Financial Management.- Empirical Investigation of Random Forest Model's Predictive Capability for A-share Banking and Food Industry Stocks.- Research on the Impact of Digital Inclusive Finance Combined with Intelligent Analysis Model on enterprise Green Technology Innovation.- Machine Learning-Based Analysis of the Impact Effect of Digital Transformation in Commercial Banks on Digital Financial Development.- Research on Quantitative Investment Strategy Based on Multifactor Stock Selection and Transformer-SVR Fusion Modeling.- LSTM-based Stock Price Prediction for New Energy Vehicles.- A Study on Intelligent Evaluation of Teaching Financial Statement Analysis Based on BP Neural Networks.- Research on Intelligent Identification and Prediction Model of Enterprise Financial Risk Based on Multimodal Machine Learning.- Research on High-dimensional Feature Selection and Asset Allocation Optimization Algorithm for Financial Big Data.- Student Behavior Pattern Mining and Management Optimization in Colleges and Universities Based on Big Data Analysis.- Construction of Intelligent English Writing Scoring Model Integrating Natural Language Processing and Semantic Analysis.- Application of Intelligent Knowledge Mining Technology in English Online Teaching.- Talent Intelligent Recommendation Method Based on Big Data and Knowledge Graph.- Research on the Intelligent Algorithm Modeling of the Risk Assessment of Sports Injuries in Traditional National Sports.- Research on Visual Understanding Algorithm of Art Aided Design Scene in Digital Background.- Intelligent Generation and Optimization of China Traditional Cultural Content Based on Large-scale Pre-training Model.- Intelligent Algorithm and Model Application in the Construction of Digital Ecosystem of Rural Cultural and Creative Product Design.- Research on the Dissemination of Traditional Chinese Cultural Art in the Context of Digital Media.



About the Author :

Rumen Mironov received his M.Sc. and Ph.D. in telecommunications from Technical University of Sofia and M.Sc. in applied mathematics and informatics from Faculty of Applied Mathematics and Informatics. Currently, he is Associate Professor in the Faculty of Telecommunications and teaches programming in object oriented languages, digital signal processing, digital image processing, audio and video communications over Internet, and other subjects. His current research focuses on multidimensional signal processing, pattern recognition, audio and video communications, information systems, computer graphics, and programming languages. During his research activities, Dr. Mironov participated in more than 20 national and international projects and was the PI of several of them. He published more than 120 papers. Dr. Mironov is Member of IJBST Journal Group, Bulgarian Association of Pattern Recognition (IAPR), and Bulgarian Union of Automation and Automation Systems.

Roumiana Kountcheva is Vice President of TK Engineering. She got her M.Sc. and Ph.D. at the Technical University of Sofia, Bulgaria, and became Senior Researcher (SR) in 1993. She had two post-doc trainings in Japan (Fujitsu, 1977 and Fanuc, 1980). She has more than 220 publications (including 35 book chapters and 5 patents) and presented 28 plenary speeches at international conferences and workshops. She is Member of IRIEM, IDSAI, IJBST Journal Group, and Bulgarian Association for Pattern Recognition. R. Kountcheva participated as PI, Co-PI, and Team Member of 47 scientific research projects, from which 14 were international. She is Co-Editor of several SIs in Symmetry MDPI and Reviewer of WSEAS conferences and journals. Also, R. Kountcheva edited several books for Springer SIST series.

Ivo Draganov received B.Sc., M.Sc., and Ph.D. in telecommunications from Technical University of Sofia, Bulgaria, in 2003, 2005, and 2009. Currently, he is Associate Professor in the Faculty of Telecommunications and teaches programming in assembler, digital design, measurements in telecommunications, audio systems and speech coding, multimedia systems, digital video broadcasting, and other subjects. His main areas of scientific research are digital image processing, pattern recognition, multimedia systems, and neural networks. He is Member of the Editorial Board of the Computer and Communications Engineering Journal. During his research activities, Dr. Draganov participated in more than 10 national and international projects and published more than 100 papers.

Kazumi Nakamatsu received the Ms.Eng. and Dr.Sci. from Shizuoka University and Kyushu University, Japan, respectively. His research interests encompass various kinds of logic and their applications to computer science, especially paraconsistent annotated logic programs and their applications. He has developed some paraconsistent annotated logic programs called Annotated Logic Program with Strong Negation (ALPSN), Vector ALPSN (VALPSN), Extended VALPSN (EVALPSN) and before-after EVALPSN (bf-EVALPSN) recently and applied them to various intelligent systems such as a safety verification based railway interlocking control system and process order control. He is Author of over 150 papers and 20 book chapters and 10 edited books published by prominent publishers. Kazumi Nakamatsu has chaired various international conferences, workshops, and invited sessions, and he has been Member of numerous international program committees of workshops and conferences in the area of Computer Science.


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Product Details
  • ISBN-13: 9783032202710
  • Publisher: Springer Nature Switzerland AG
  • Publisher Imprint: Springer Nature Switzerland AG
  • ISBN-10: 303220271X
  • Publisher Date: 25 May 2026


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