Mustafa Munir

457 total citations · 1 hit paper
10 papers, 154 citations indexed

About

Mustafa Munir is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Mustafa Munir has authored 10 papers receiving a total of 154 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 2 papers in Electrical and Electronic Engineering and 1 paper in Computer Networks and Communications. Recurrent topics in Mustafa Munir's work include Advanced Neural Network Applications (3 papers), Visual Attention and Saliency Detection (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). Mustafa Munir is often cited by papers focused on Advanced Neural Network Applications (3 papers), Visual Attention and Saliency Detection (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). Mustafa Munir collaborates with scholars based in United States and South Korea. Mustafa Munir's co-authors include Md Mostafijur Rahman, Diana Marculescu, Radu Mărculescu, Md. Mostafijur Rahman, Ulaş Bağcı, Massoud Pedram, Debesh Jha, Shahin Nazarian and Tanvir Mahmud and has published in prestigious journals such as IEEE Access and IEEE Transactions on Applied Superconductivity.

In The Last Decade

Mustafa Munir

9 papers receiving 149 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

EMCAD: Efficient Multi-Scale Convolutional Attention Decoding for Medical Image Segmentation

2024 101 citations Md Mostafijur Rahman, Mustafa Munir et al. profile →

Peers

Mustafa Munir

CVPR

AI

RNMI

NEURO

BE

Renkai Wu China

Pengshuai Yin China

Pei Yu China

Bin Dong China

Zhenxi Zhang China

Wenchi Ma United States

Shuli Cheng China

Alejandro Mora-Rubio Colombia

Noel E. O’Connor Ireland

Peilun Shi Hong Kong

Renkai Wu China

Mustafa Munir

81 ×1.0

CVPR

64 ×1.7

AI

31 ×1.1

RNMI

20 ×1.1

NEURO

10 ×0.7

BE

Citations per year, relative to Mustafa Munir Mustafa Munir (= 1×) peers Renkai Wu

Countries citing papers authored by Mustafa Munir

Since Specialization

Citations

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

Fields of papers citing papers by Mustafa Munir

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mustafa Munir

This figure shows the co-authorship network connecting the top 25 collaborators of Mustafa Munir. A scholar is included among the top collaborators of Mustafa Munir 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 Mustafa Munir. Mustafa Munir is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Mahmud, Tanvir, Mustafa Munir, Radu Mărculescu, & Diana Marculescu. (2025). Ada-VE: Training-Free Consistent Video Editing Using Adaptive Motion Prior. 940–949.

2.

Munir, Mustafa, Md Mostafijur Rahman, & Radu Mărculescu. (2025). RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone. 8302–8312. 1 indexed citations

3.

Munir, Mustafa, et al.. (2024). GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs. 6118–6127. 9 indexed citations

4.

Rahman, Md Mostafijur, Mustafa Munir, & Diana Marculescu. (2024). EMCAD: Efficient Multi-Scale Convolutional Attention Decoding for Medical Image Segmentation. 11769–11779. 101 indexed citations breakdown →

5.

Rahman, Md. Mostafijur, Mustafa Munir, Debesh Jha, Ulaş Bağcı, & Radu Mărculescu. (2024). PP-SAM: Perturbed Prompts for Robust Adaption of Segment Anything Model for Polyp Segmentation. 4989–4995. 3 indexed citations

6.

Munir, Mustafa, et al.. (2024). Scaling Graph Convolutions for Mobile Vision. 5857–5865. 4 indexed citations

7.

Munir, Mustafa, et al.. (2024). Three Decades of Low Power: From Watts to Wisdom. IEEE Access. 12. 19447–19458. 2 indexed citations

8.

Munir, Mustafa, et al.. (2023). MobileViG: Graph-Based Sparse Attention for Mobile Vision Applications. 2211–2219. 30 indexed citations

9.

Munir, Mustafa, et al.. (2021). qMC. 259–264. 2 indexed citations

10.

Munir, Mustafa, et al.. (2021). A Logic Verification Framework for SFQ and AQFP Superconducting Circuits. IEEE Transactions on Applied Superconductivity. 31(9). 1–11. 2 indexed citations

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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