Naveed Ejaz

1.4k citations
54 papers · 1.0k · h-index 17

Impact in

Papers in

Naveed Ejaz

48 papers receiving 970 citations

Peers

Naveed Ejaz
Comparison fields: 5 of 100
  • Computer Vision and Pattern Recognition 532
  • Signal Processing 228
  • Industrial and Manufacturing Engineering 69
  • Media Technology 53
  • Computer Networks and Communications 113
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Peerapong Uthansakul Thailand
Avinash Sharma India
Minas Dasygenis Greece
Gaurav Meena India
Jamal Ahmad Dargham Malaysia
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Rahul Mishra India
Vimal Shanmuganathan India
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Citations per field
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Citations per year

Countries citing papers authored by Naveed Ejaz

Since Specialization
Citations

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

Fields of papers citing papers by Naveed Ejaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Naveed Ejaz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Naveed Ejaz Line = papers co-authored together Naveed Ejaz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012143
2 2012139
3 201686
4 201081
5 201269
6 201345
7 201339
8 202036
9 202329
10 201129
11 202228
12 201222
13 200821
14 201819
15 201819
16 201219
17 201318
18 202213
19 200712
20 201212

About Naveed Ejaz

Naveed Ejaz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Mechanical Engineering and Sociology and Political Science, having authored 54 papers that have together received 1.0k indexed citations. Recurring topics across this work include Video Analysis and Summarization (11 papers), Multimedia Communication and Technology (6 papers), Human Pose and Action Recognition (5 papers), Music and Audio Processing (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Mechanical Failure Analysis and Simulation (5 papers), Anomaly Detection Techniques and Applications (4 papers) and Remote Sensing and LiDAR Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (532 citations), Signal Processing (228 citations), Industrial and Manufacturing Engineering (69 citations), Media Technology (53 citations) and Computer Networks and Communications (113 citations). Naveed Ejaz has collaborated with scholars based in Pakistan, South Korea and Canada. Frequent co-authors include Sung Wook Baik, Irfan Mehmood, Waleed Ejaz, Najam Ul Hasan, Muhammad Sajjad, Salimur Choudhury, Hyung Ham Kim, Hyung Seok Kim, Minho Jo and Alagan Anpalagan. Their work appears in journals such as IEEE Access, Engineering Failure Analysis, Multimedia Tools and Applications, Sensors and Artificial Intelligence Review.

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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