Salah Bourennane – författare

This book contains the proceedings of the 5th International Conference on Geoinformatics and Data Analysis (ICGDA 2022), held in January 21–23, Paris, France. Geoinformatics helps to support basic scientific inquiry as well as address the complex social and environmental challenges. It becomes very important technology to decision-makers across a wide range of disciplines such as computer science, information technology, software engineering, biogeography, geography, conservation, architecture, spatial analysis and reinforcement learning. The papers included in this proceeding share the latest research results and practical application examples on the methodologies and algorithms in the area of geoinformatics and data analysis, including software and information engineering, environmental geography and geographic information system, which makes the book a valuable reference for researchers, engineers and university students who are working in the field.

This book contains the proceedings of the 5th International Conference on Geoinformatics and Data Analysis (ICGDA 2022), held in January 21–23, Paris, France. Geoinformatics helps to support basic scientific inquiry as well as address the complex social and environmental challenges. It becomes very important technology to decision-makers across a wide range of disciplines such as computer science, information technology, software engineering, biogeography, geography, conservation, architecture, spatial analysis and reinforcement learning. The papers included in this proceeding share the latest research results and practical application examples on the methodologies and algorithms in the area of geoinformatics and data analysis, including software and information engineering, environmental geography and geographic information system, which makes the book a valuable reference for researchers, engineers and university students who are working in the field.

This book gathers peer reviewed and high-quality papers presented at 2025 8th International Conference on Geoinformatics and Data Analysis, held from April 4 to 6, 2025 in Nice, France. The topics discussed in the book are grouped into three sections including Intelligent Communication Navigation System and Positioning Algorithm Based on Geographic Location, Geospatial Monitoring and Urban Planning Based on Remote Sensing Technology, Modern Geographic Information System and Data Analysis. This book serves as a valuable reference for young scholars and researchers who are working in the fields of Geoinformatics and Data Analysis.

This book gathers peer reviewed and high-quality papers presented at 2025 8th International Conference on Geoinformatics and Data Analysis, held from April 4 to 6, 2025 in Nice, France. The topics discussed in the book are grouped into three sections including Intelligent Communication Navigation System and Positioning Algorithm Based on Geographic Location, Geospatial Monitoring and Urban Planning Based on Remote Sensing Technology, Modern Geographic Information System and Data Analysis. This book serves as a valuable reference for young scholars and researchers who are working in the fields of Geoinformatics and Data Analysis.

This book presents a selection of high-quality, peer-reviewed papers from the 9th International Conference on Geoinformatics and Data Analysis (ICGDA 2026), held in Lyon, France, from April 13-15, 2026. This book covers a wide range of topics including Geospatial Data Analysis and Modeling, Geospatial Multimodal Data Analysis, Modeling Methods, and Security Management, Remote Sensing-based Spatial Data Analysis and Intelligent Communication Technologies, Geographic information retrieval, Theories and algorithms in GIS. It serves as an essential reference for researchers, scholars, and professionals working in the fields of geoinformatics and data analysis.

This book constitutes the refereed proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2008, held in Juan-les-Pins, France, in October 2008. The 33 revised full papers and 69 posters presented were carefully reviewed and selected from 179 submissions. The papers are organized in topical sections on image and video coding; systems and applications; video processing; filtering and restoration; segmentation and feature extraction; tracking, scene understanding and computer vision; medical imaging; and biometrics and surveillance.

This book constitutes the refereed proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2008, held in Juan-les-Pins, France, in October 2008. The 33 revised full papers and 69 posters presented were carefully reviewed and selected from 179 submissions. The papers are organized in topical sections on image and video coding; systems and applications; video processing; filtering and restoration; segmentation and feature extraction; tracking, scene understanding and computer vision; medical imaging; and biometrics and surveillance.

This book targets an audience with a basic understanding of deep learning, its architectures, and its application in the multimedia domain. Background in machine learning is helpful in exploring various aspects of deep learning. Deep learning models have a major impact on multimedia research and raised the performance bar substantially in many of the standard evaluations. Moreover, new multi-modal challenges are tackled, which older systems would not have been able to handle. However, it is very difficult to comprehend, let alone guide, the process of learning in deep neural networks, there is an air of uncertainty about exactly what and how these networks learn. By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.

This book targets an audience with a basic understanding of deep learning, its architectures, and its application in the multimedia domain. Background in machine learning is helpful in exploring various aspects of deep learning. Deep learning models have a major impact on multimedia research and raised the performance bar substantially in many of the standard evaluations. Moreover, new multi-modal challenges are tackled, which older systems would not have been able to handle. However, it is very difficult to comprehend, let alone guide, the process of learning in deep neural networks, there is an air of uncertainty about exactly what and how these networks learn. By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.