Farhan Akram
Impact in
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- Medical Image Segmentation Techniques
- Image and Object Detection Techniques
- Artificial Intelligence top 5%
- AI in cancer detection
- Anomaly Detection Techniques and Applications
Papers in
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- Medical Image Segmentation Techniques 12
- Image and Object Detection Techniques 4
- Image and Signal Denoising Methods 3
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- AI in cancer detection 6
- Co-authors
- Domènec Puig (8 shared papers)Kwang Nam Choi (12 shared papers)Vivek Kumar Singh (5 shared papers)Hatem A. Rashwan (5 shared papers)Miguel Ángel García (3 shared papers)Mohamed Abdel‐Nasser (4 shared papers)Hwee Kuan Lee (3 shared papers)Md. Mostafa Kamal Sarker (5 shared papers)
- Journals
- IEEE Access (3 papers)Expert Systems with Applications (3 papers)Scientific Reports (2 papers)PLoS ONE (2 papers)Lung Cancer (2 papers)
- Partner nations
- SpainSouth KoreaNetherlands
In The Last Decade
Farhan Akram
29 papers receiving 495 citations
Peers
Comparison fields: 5 of 79
- Computer Vision and Pattern Recognition 225
- Artificial Intelligence 239
- Radiology, Nuclear Medicine and Imaging 135
- Media Technology 57
- Neurology 33
Countries citing papers authored by Farhan Akram
This map shows the geographic impact of Farhan Akram'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 Akram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Farhan Akram more than expected).
Fields of papers citing papers by Farhan Akram
This network shows the impact of papers produced by Farhan Akram. 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 Akram. The network helps show where Farhan Akram may publish in the future.
Co-authors
The 25 scholars most cited alongside Farhan Akram, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 66 | |
| 2 | 2019 | 56 | |
| 3 | 2020 | 53 | |
| 4 | 2019 | 48 | |
| 5 | 2017 | 35 | |
| 6 | 2019 | 32 | |
| 7 | 2017 | 32 | |
| 8 | 2022 | 19 | |
| 9 | 2020 | 18 | |
| 10 | 2017 | 17 | |
| 11 | 2015 | 16 | |
| 12 | 2014 | 16 | |
| 13 | 2016 | 15 | |
| 14 | 2023 | 14 | |
| 15 | 2013 | 12 | |
| 16 | 2021 | 11 | |
| 17 | 2017 | 9 | |
| 18 | A Preprocessing Algorithm for the CAD System of Mammograms Using the Active Contour Method | 2013 | 8 |
| 19 | 2013 | 6 | |
| 20 | 2019 | 6 |
About Farhan Akram
Farhan Akram is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Biophysics and Oncology, having authored 30 papers that have together received 512 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (12 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (6 papers), Cell Image Analysis Techniques (5 papers), Image and Object Detection Techniques (4 papers), Image and Signal Denoising Methods (3 papers), Advanced Image Fusion Techniques (2 papers) and Cutaneous Melanoma Detection and Management (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (225 citations), Artificial Intelligence (239 citations), Radiology, Nuclear Medicine and Imaging (135 citations), Media Technology (57 citations) and Neurology (33 citations). Farhan Akram has collaborated with scholars based in Spain, South Korea and Netherlands. Frequent co-authors include Domènec Puig, Kwang Nam Choi, Vivek Kumar Singh, Hatem A. Rashwan, Miguel Ángel García, Mohamed Abdel‐Nasser, Hwee Kuan Lee, Md. Mostafa Kamal Sarker, Nidhi Pandey and Sojeong Park. Their work appears in journals such as IEEE Access, Expert Systems with Applications, Scientific Reports, PLoS ONE and Lung Cancer.
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.