Countries where authors publish in High-Confidence Computing
Since Specialization
Citations
This map shows the geographic impact of research published in High-Confidence Computing. 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 papers published in High-Confidence Computing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites High-Confidence Computing more than expected).
Fields of papers published in High-Confidence Computing
This network shows the impact of papers published in High-Confidence Computing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in High-Confidence Computing.
About High-Confidence Computing
The 202 papers published in High-Confidence Computing in the last decades have received a total of 2.3k indexed citations . Papers published in High-Confidence Computing usually cover Information Systems (84 papers), Artificial Intelligence (110 papers), Computer Networks and Communications (69 papers), Signal Processing (21 papers) and Computer Vision and Pattern Recognition (37 papers) specifically the topics of Blockchain Technology Applications and Security (45 papers), Privacy-Preserving Technologies in Data (44 papers), Cryptography and Data Security (39 papers), IoT and Edge/Fog Computing (27 papers), Network Security and Intrusion Detection (20 papers), Advanced Malware Detection Techniques (18 papers), Cloud Data Security Solutions (16 papers) and Adversarial Robustness in Machine Learning (14 papers). The most active scholars publishing in High-Confidence Computing are Yue Zhang, Yifan Yao, Yuanfang Cai, Jinhao Duan, Zhibo Sun, Kaidi Xu, Xiuzhen Cheng, Qun Li, Qi Xia and Zeyi Tao.
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.