Danni Ai

126 papers and 1.1k indexed citations i.

About

Danni Ai is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Danni Ai has authored 126 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Computer Vision and Pattern Recognition, 46 papers in Radiology, Nuclear Medicine and Imaging and 29 papers in Biomedical Engineering. Recurrent topics in Danni Ai’s work include Medical Image Segmentation Techniques (49 papers), Retinal Imaging and Analysis (23 papers) and Robotics and Sensor-Based Localization (14 papers). Danni Ai is often cited by papers focused on Medical Image Segmentation Techniques (49 papers), Retinal Imaging and Analysis (23 papers) and Robotics and Sensor-Based Localization (14 papers). Danni Ai collaborates with scholars based in China, United Kingdom and Japan. Danni Ai's co-authors include Jian Yang, Yongtian Wang, Jingfan Fan, Hong Song, Yong Huang, Songyuan Tang, Syed Furqan Qadri, Mubashir Ahmad, Yitian Zhao and Xuehu Wang and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Co-authorship network of co-authors of Danni Ai i

Fields of papers citing papers by Danni Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danni Ai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Danni Ai. The network helps show where Danni Ai may publish in the future.

Countries citing papers authored by Danni Ai

Since Specialization
Citations

This map shows the geographic impact of Danni Ai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Danni Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danni Ai more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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2025