Privacy Protection

Annotating the scene text in the PRIVATY-TEXT-IMAGE dataset was done in Adobe Photoshop.   To maintain the rationality of the annotation operation, the images' aesthetics, and the textures' consistency around the deleted text areas, we utilized the content-aware fill feature of Photoshop.   This feature can enhance intelligent editing and modification capabilities during the image processing, automatically analyze the image content around the private text areas, and generate matching filling content to make the images look more natural and complete.  

Annotating the scene text in the PRIVATY-TEXT-IMAGE dataset was done in Adobe Photoshop.   To maintain the rationality of the annotation operation, the images' aesthetics, and the textures' consistency around the deleted text areas, we utilized the content-aware fill feature of Photoshop.   This feature can enhance intelligent editing and modification capabilities during the image processing, automatically analyze the image content around the private text areas, and generate matching filling content to make the images look more natural and complete.  

Annotating the scene text in the PRIVATY-TEXT-IMAGE dataset was done in Adobe Photoshop.   To maintain the rationality of the annotation operation, the images' aesthetics, and the textures' consistency around the deleted text areas, we utilized the content-aware fill feature of Photoshop.   This feature can enhance intelligent editing and modification capabilities during the image processing, automatically analyze the image content around the private text areas, and generate matching filling content to make the images look more natural and complete.  

Annotating the scene text in the PRIVATY-TEXT-IMAGE dataset was done in Adobe Photoshop.   To maintain the rationality of the annotation operation, the images' aesthetics, and the textures' consistency around the deleted text areas, we utilized the content-aware fill feature of Photoshop.   This feature can enhance intelligent editing and modification capabilities during the image processing, automatically analyze the image content around the private text areas, and generate matching filling content to make the images look more natural and complete.  

This paper conducts a systematic bibliometric analysis in the Artificial Intelligence (AI) domain to explore privacy protection research as AI technologies integrate and data privacy concerns rise. Understanding evolutionary patterns and current trends in this research is crucial. Leveraging bibliometric techniques, the authors analyze 8,322 papers from the Web of Science (WoS) database, spanning 1990 to 2023.

This paper conducts a systematic bibliometric analysis in the Artificial Intelligence (AI) domain to explore privacy protection research as AI technologies integrate and data privacy concerns rise. Understanding evolutionary patterns and current trends in this research is crucial. Leveraging bibliometric techniques, the authors analyze 3,061 papers from the Web of Science (WoS) database, spanning 1994 to 2023.