Tehseen Zia

1.3k citations
50 papers · 875 indexed · h-index 16
Topics
Adversarial Robustness in Machine Learning (5 papers)Face and Expression Recognition (5 papers)COVID-19 diagnosis using AI (5 papers)

In The Last Decade

Tehseen Zia

48 papers receiving 824 citations

Peers

Tehseen Zia
Comparison fields: 5 of 111
  • Artificial Intelligence 339
  • Computer Vision and Pattern Recognition 199
  • Electrical and Electronic Engineering 177
  • Radiology, Nuclear Medicine and Imaging 152
  • Signal Processing 118
Replace Mubarak Alrashoud with:
Mubarak Alrashoud Saudi Arabia
Sadaqat Ur Rehman China
Hrudaya Kumar Tripathy India
Lubna A. Gabralla Saudi Arabia
Michał Wieczorek Poland
Jakub Siłka Poland
Kishor Datta Gupta United States
Fahad Taha AL‐Dhief Malaysia
Ahmed I. Taloba Saudi Arabia
Mohammed Nasser Al‐Mhiqani Malaysia
Tehseen Zia relative to Mubarak Alrashoud Saudi Arabia Mubarak Alrashoud's profile →
Citations per field
00.5×10×15.5×
Mubarak Alrashoud · 1×
Citations per year

Countries citing papers authored by Tehseen Zia

Since Specialization
Citations

This map shows the geographic impact of Tehseen Zia'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 Tehseen Zia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tehseen Zia more than expected).

Fields of papers citing papers by Tehseen Zia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tehseen Zia. 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 Tehseen Zia. The network helps show where Tehseen Zia may publish in the future.

Co-authorship network of co-authors of Tehseen Zia

This figure shows the co-authorship network connecting the top 25 collaborators of Tehseen Zia. A scholar is included among the top collaborators of Tehseen Zia based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tehseen Zia. Tehseen Zia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 2
4 2
5 49
6 3
7 35
8 67
9 19
10 8
11 11
12 15
13 41
14 10
15 6
16
Comparative Study of Feature Selection Approaches for Urdu Text Categorization
50
17 30
18 1
19 98
20 15

About Tehseen Zia

Tehseen Zia is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 50 papers that have together received 875 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (5 papers), Face and Expression Recognition (5 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Health Informatics (15 citations), Signal Processing (118 citations) and Artificial Intelligence (339 citations). Tehseen Zia has collaborated with scholars based in Pakistan, United Kingdom and China. Frequent co-authors include Adeel Zaidi, Mubeen Ghafoor, Dietmar Bruckner, Qaiser Abbas, Muhammad Pervez Akhter, Friederich Kupzog, Ghufran Ahmed, M. Saqib Nawaz, M. Ikram Ullah Lali and David Windridge. Their work appears in journals such as PLoS ONE, Scientific Reports and IEEE Access.

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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