Artificial Intelligence-Driven Methods for Remote Sensing Target and Object Detection

Dear Colleagues,

Remote sensing image includes a rich description of the earth’s surface in various modalities (hyperspectral data, high resolution data, multispectral data, synthetic aperture radar (SAR) data, etc.). Remote sensing target detection or object detection is to determine whether there are targets or objects of interest in the image, playing a decisive role in resource detection, environmental monitoring, urban planning, national security, agriculture, forestry, climate, hydrologand, etc. In recent years, artificial intelligence (AI) has achieved considerable development and been successfully applied for various applications, such as regression, clustering, classification, etc. Although AI-driven approaches can handle massive quantity of data acquired by remote sensors, they require many high-quality labeled samples to deal with remote sensing big data, leading to fragile results. That is, AI-driven approaches with strong ability of feature extraction have limited performance and are still far from practical demands. Thus, target detection or object detection in the presence of complicated background with limited labeled samples remains a challenging mission. There is still much room for research on remote sensing target detection and object detection. The main goal of this special issue is to address advanced topics related to remote sensing target detection and object detection.Topics of interests include but are not limited to the following:

• New AI-driven methods for remote sensing data, such as GNN, transformer, etc.;
• New remote sensing datasets, including hyperspectral, high resolution, SAR datasets, etc.;
• Machine learning techniques for remote sensing applications, such as domain adaptation, few-shot learning, manifold learning, metric learning;
• Machine learning-based drone detection and fine-grained detection;
• Target detection, object detection, and anomaly detection;
• Data-driven applications in remote sensing;
• Technique reviews on related topics.

Dr. Yanni Dong
Dr. Xiaochen Yang
Prof. Dr. Qian Du
Guest Editors

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