Special Issue on “Computer Vision for Remote Sensing”
• 大类 : 工程技术 - 3区
• 小类 : 计算机：人工智能 - 3区
• 小类 : 工程：电子与电气 - 3区
Currently, massive streams of earth observation data are being systematically collected from different cutting-edge optical and radar sensors, on-board satellite, aerial and terrestrial platforms.
These exponentially increasing amount of data including both images and video sequences of different spatial, spectral and temporal resolutions, monitor constantly the earth's surface. In order to fully exploit these datasets and timely deliver crucial information for numerous engineering, environmental, safety and security applications, novel computer vision and machine learning methods are required towards efficiently dissecting and interpreting the data, drawing conclusions
that the broader public can turn into action.
This special issue aims at showcasing the latest advances and trends in computer vision and machine learning algorithms for remote sensing data exploitation. Its scope is interdisciplinary and seeks collaborative contributions from academia and industrial experts in the areas of geoscience
and remote sensing, signal processing, computer vision, machine learning and data science.
Manuscripts are solicited to address a wide range of topics on computer vision techniques and remote sensing data understanding, including but not limited to the following:
• Performance Evaluation and Benchmark Datasets
• Multi-sensor Data Analysis, 3D Computer Vision
• Object/ Target Detection, Recognition and Identification
• Transfer Learning and Statistical Learning Methods
• Big Data, Large Scale Methods
• Deep Learning Techniques
• Motion and Tracking, Space Video Analytics
• Time series data analysis, change detection
• Integration of ground and non-image data in remote sensing pipelines