Imran Ashraf

52 papers receiving 1.4k citations

Imran Ashraf's Hit Papers

Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists 2020 · 306 citations
3060+2+4Years since publication100200300

Peers

Imran Ashraf
Comparison fields: 5 of 107
  • Neurology 321
  • Computer Vision and Pattern Recognition 464
  • Artificial Intelligence 723
  • Health Informatics 30
  • Radiology, Nuclear Medicine and Imaging 287
Replace Muhammad Nazir with:
Muhammad Nazir Pakistan
Samir Elmougy Egypt
Pengtao Xie United States
S. Ravi India
Marco Grangetto Italy
Yuk Ying Chung Australia
Ahmed Mohammed Alghamdi Saudi Arabia
El-Sayed M. El-Horbaty Egypt
Sumeet Dua United States
Yaoliang Yu Canada
Imran Ashraf relative to Muhammad Nazir Pakistan Muhammad Nazir's profile →
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Citations per year

Countries citing papers authored by Imran Ashraf

Since Specialization
Citations

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

Fields of papers citing papers by Imran Ashraf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists
Hit paper breakdown →
2020306
2 2020102
3 202081
4 202280
5 202174
6 202065
7 201760
8 202255
9 201754
10 202347
11 202145
12 202243
13 201942
14 202137
15 202232
16
A Unified Design of ACO and Skewness based Brain Tumor Segmentation and Classification from MRI Scans
202031
17 201829
18 202325
19 201925
20 201820

About Imran Ashraf

Imran Ashraf is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Hardware and Architecture, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 58 papers that have together received 1.5k indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (11 papers), Parallel Computing and Optimization Techniques (10 papers), Quantum Information and Cryptography (8 papers), Embedded Systems Design Techniques (8 papers), Gastrointestinal Bleeding Diagnosis and Treatment (7 papers), Colorectal Cancer Screening and Detection (6 papers), Quantum-Dot Cellular Automata (5 papers) and Brain Tumor Detection and Classification (5 papers). The work is most often cited by research in Neurology (321 citations), Computer Vision and Pattern Recognition (464 citations), Artificial Intelligence (723 citations), Health Informatics (30 citations) and Radiology, Nuclear Medicine and Imaging (287 citations). Imran Ashraf has collaborated with scholars based in Pakistan, Saudi Arabia and South Korea. Frequent co-authors include Muhammad Attique Khan, Majed Alhaisoni, Robertas Damaševičius, Amjad Rehman, Syed Ahmad Chan Bukhari, Rafał Scherer, Carmen G. Almudéver, Koen Bertels, Lingling Lao and Xiang Fu. Their work appears in journals such as IEEE Access, Computers, materials & continua/Computers, materials & continua (Print), Scientific Reports, Journal Of Big Data and Applied Sciences.

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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