105 citations · 233 across the 6 of their papers we have counts for
6 papers
Can Deep Network Balance Copy-Move Forgery Detection and Distinguishment?
Shizhen Chang
Copy-move forgery detection is a crucial research area within digital image forensics, as it focuses on identifying instances where objects in an image are duplicated and placed in…
Dsfer-Net: A Deep Supervision and Feature Retrieval Network for Bitemporal Change Detection Using Modern Hopfield Networks
Shizhen Chang, Michael Kopp, Pedram Ghamisi +1
Change detection, an essential application for high-resolution remote sensing images, aims to monitor and analyze changes in the land surface over time. Due to the rapid increase i…
Changes to Captions: An Attentive Network for Remote Sensing Change Captioning
Shizhen Chang, Pedram Ghamisi
In recent years, advanced research has focused on the direct learning and analysis of remote sensing images using natural language processing (NLP) techniques. The ability to accur…
AI Security for Geoscience and Remote Sensing: Challenges and Future Trends
Yonghao Xu, Tao Bai, Weikang Yu +3
Recent advances in artificial intelligence (AI) have significantly intensified research in the geoscience and remote sensing (RS) field. AI algorithms, especially deep learning-bas…
Sketched Multi-view Subspace Learning for Hyperspectral Anomalous Change Detection
Shizhen Chang, Michael Kopp, Pedram Ghamisi
In recent years, multi-view subspace learning has been garnering increasing attention. It aims to capture the inner relationships of the data that are collected from multiple sourc…
Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly Detection
Shizhen Chang, Pedram Ghamisi
Recently, many collaborative representation-based (CR) algorithms have been proposed for hyperspectral anomaly detection. CR-based detectors approximate the image by a linear combi…