Fath U Min Ullah

28 papers and 955 indexed citations i.

About

Fath U Min Ullah is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Fath U Min Ullah has authored 28 papers receiving a total of 955 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 13 papers in Electrical and Electronic Engineering and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Fath U Min Ullah’s work include Energy Load and Power Forecasting (10 papers), Anomaly Detection Techniques and Applications (8 papers) and Video Surveillance and Tracking Methods (8 papers). Fath U Min Ullah is often cited by papers focused on Energy Load and Power Forecasting (10 papers), Anomaly Detection Techniques and Applications (8 papers) and Video Surveillance and Tracking Methods (8 papers). Fath U Min Ullah collaborates with scholars based in South Korea, United Kingdom and Saudi Arabia. Fath U Min Ullah's co-authors include Sung Wook Baik, Ijaz Ul Haq, Amin Ullah, Mi Young Lee, Khan Muhammad, Noman Khan, Tanveer Hussain, Zulfiqar Ahmad Khan, Seungmin Rho and Waseem Ullah and has published in prestigious journals such as Expert Systems with Applications, Sensors and Energy and Buildings.

In The Last Decade

Co-authorship network of co-authors of Fath U Min Ullah i

Fields of papers citing papers by Fath U Min Ullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fath U Min Ullah. 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 Fath U Min Ullah. The network helps show where Fath U Min Ullah may publish in the future.

Countries citing papers authored by Fath U Min Ullah

Since Specialization
Citations

This map shows the geographic impact of Fath U Min Ullah'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 Fath U Min Ullah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fath U Min Ullah 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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