With the rapid development of deep learning technology， the information extraction methods of remotesensing images are rapidly changing from traditional statistics to data-driven intelligent interpretation. In thebackground of the rapid development of artificial intelligence technology， and supported by major projects suchas National Science and Technology Major Project of China High-resolution Earth Observation System， NationalNatural Science Foundation of China， Civil Aerospace ”14th Five-Year” Technology Pre-research Project， theauthors and their team have made a series of research achievements in the filed of intelligent interpretation andapplication technology of remote sensing images. This book starts from the development status of remote sensingimage intelligent interpretation and application technology， systematically introduces the main contents of remotesensing image intelligent interpretation and application， focusing on remote sensing image intelligent qualityimprovement， intelligent expansion and sample augmentation， object detection， fine-grained target recognition，semantic segmentation， multimodal remote sensing image joint intelligent interpretation as well as intelligentinterpretation and application platform.This book can be used as a reference book for remote sensing related majors in colleges and universities，and also for research scholars and staff in the field of remote sensing. With the rapid development of deep learning technology， the information extraction methods of remotesensing images are rapidly changing from traditional statistics to data-driven intelligent interpretation. In thebackground of the rapid development of artificial intelligence technology， and supported by major projects suchas National Science and Technology Major Project of China High-resolution Earth Observation System， NationalNatural Science Foundation of China， Civil Aerospace ”14th Five-Year” Technology Pre-research Project， theauthors and their team have made a series of research achievements in the filed of intelligent interpretation andapplication technology of remote sensing images. This book starts from the development status of remote sensingimage intelligent interpretation and application technology， systematically introduces the main contents of remotesensing image intelligent interpretation and application， focusing on remote sensing image intelligent qualityimprovement， intelligent expansion and sample augmentation， object detection， fine-grained target recognition，semantic segmentation， multimodal remote sensing image joint intelligent interpretation as well as intelligentinterpretation and application platform.
This book can be used as a reference book for remote sensing related majors in colleges and universities，and also for research scholars and staff in the field of remote sensing.
目錄：
Chapter 1 Introduction
1.1 Connotation
1.2 Development Demand
1.3 Current Development Situation
1.4 Existing Problems
1.5 Development Trend
1.6 Chapter Summary
Chapter 2 Intelligent Quality Enhancement of Remote Sensing Images
2.1 Improvement of Signal-to-Noise Ratio in Remote Sensing Images
2.2 Spatial Resolution Improvement of Remote Sensing Images
2.3 SAt/Image Despeckling Method Based on Adversarial Learning
2.4 Chapter Summary
Chapter 3 Intelligent Expansion and Sample Amplification of Remote Sensing Images
3.1 Overview
3.2 Intelligent Assisted Annotation
3.3 Intelligent Sample Expansion
3.4 Sample Self-Growth
3.5 Chapter Summary
Chapter 4 Intelligent Object Detection in Remote Sensing Images
4.1 Overview
4.2 Deep Learning Based Object Detection Framework
4.3 Object Detection Datasets in Remote Sensing Images and Evaluation Metrics
4.4 Target Representation Methods in Remote Sensing Images
4.5 Label Assignment Strategy in Remote Sensing Images
4.6 The Detection Head for Object Detection in Remote Sensing Images
4.7 Loss Function for Object Detection
4.8 Chapter Summary
Chapter 5 Fine-Grained Target Recognition of Remote Sensing Image
5.1 Overview
5.2 Challenges of Fine-Grained Recognition
5.3 Few-Shot Target Recognition of Multi-Scale Network
5.4 Classification of Highly Imbalanced Aviation Scenes
5.6 Chapter Summary
Chapter 6 Intelligent Semantic Segmentation
6.1 Overview
6.2 Design of Semantic Segmentation Model Based on Deep Learning
6.4 Chapter Summary
Chapter 7 Joint Intelligent Interpretation of Multimodal Remote Sensing Images
7.1 Overview
7.2 Muhimodal Remote Sensing Dataset Construction
7.3 Heterogeneous Remote Sensing Image Registration
7.4 Fusion and Classification of Multimodal Data
7.5 Chapter Summary
Chapter 8 Intelligent Remote Sensing Image Analysis: A Cognitive Platform for Interpretation
8.1 Overview
8.2 Platform Architecture
8.3 Platform Introduction
8.4 Chapter Summary
References
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