Farhan Ullah

435 citations
14 papers · 270 · 1 hit paper · h-index 8

Impact in

Papers in

Farhan Ullah

14 papers receiving 256 citations

Farhan Ullah's Hit Papers

Conventional to Deep Ensemble Methods for Hyperspectral Image Classification: A Comprehensive Survey 2024 · 54 citations
540+1Years since publication1020304050

Peers

Farhan Ullah
Comparison fields: 5 of 57
  • Media Technology 105
  • Computer Vision and Pattern Recognition 129
  • Atmospheric Science 43
  • Health Informatics 3
  • Information Systems 36
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Ling Tan China
Telagarapu Prabhakar India
Jeripothula Prudviraj India
Peng Han China
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Yuelong Xia China
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Countries citing papers authored by Farhan Ullah

Since Specialization
Citations

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

Fields of papers citing papers by Farhan Ullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Farhan Ullah, 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 Farhan Ullah Line = papers co-authored together Farhan Ullah links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 200387
2
Conventional to Deep Ensemble Methods for Hyperspectral Image Classification: A Comprehensive Survey
Hit paper breakdown →
202454
3 201929
4 202323
5 202022
6 202317
7 202410
8 20208
9 20257
10 20206
11 20243
12 20252
13 20171
14 20251

About Farhan Ullah

Farhan Ullah is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Artificial Intelligence, Atmospheric Science and Computer Networks and Communications, having authored 14 papers that have together received 270 indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (6 papers), Remote Sensing and Land Use (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Caching and Content Delivery (2 papers), Image Retrieval and Classification Techniques (2 papers), Infrared Target Detection Methodologies (2 papers), Recommender Systems and Techniques (2 papers) and Image and Video Quality Assessment (1 paper). The work is most often cited by research in Media Technology (105 citations), Computer Vision and Pattern Recognition (129 citations), Atmospheric Science (43 citations), Health Informatics (3 citations) and Information Systems (36 citations). Farhan Ullah has collaborated with scholars based in China, Saudi Arabia and Kazakhstan. Frequent co-authors include Shun’ichi Kaneko, Rehan Ullah Khan, Khalil Khan, Irfan Ullah, Bofeng Zhang, Salabat Khan, Giovanni Pau, Salim El Khediri, Muhammad Attique and Farhan Amin. Their work appears in journals such as IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Access, IEEE Transactions on Consumer Electronics, IEEE Communications Surveys & Tutorials and Sensors.

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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