Imen Charfi

967 total citations · 1 hit paper
8 papers, 625 citations indexed

About

Imen Charfi is a scholar working on Computer Vision and Pattern Recognition, Neurology and Urban Studies. According to data from OpenAlex, Imen Charfi has authored 8 papers receiving a total of 625 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 4 papers in Neurology and 3 papers in Urban Studies. Recurrent topics in Imen Charfi's work include Brain Tumor Detection and Classification (4 papers), Advanced Computing and Algorithms (3 papers) and Advanced Neural Network Applications (3 papers). Imen Charfi is often cited by papers focused on Brain Tumor Detection and Classification (4 papers), Advanced Computing and Algorithms (3 papers) and Advanced Neural Network Applications (3 papers). Imen Charfi collaborates with scholars based in Tunisia, France and Saudi Arabia. Imen Charfi's co-authors include Mohamed Atri, Wadhah Ayadi, Wajdi Elhamzi, Johel Mitéran, Rached Tourki, Julien Dubois, Julien Dubois and Barthélémy Heyrman and has published in prestigious journals such as Biomedical Signal Processing and Control, The Visual Computer and Neural Processing Letters.

In The Last Decade

Imen Charfi

8 papers receiving 589 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.

Deep CNN for Brain Tumor Classification

2021 247 citations Wadhah Ayadi, Wajdi Elhamzi et al. Neural Processing Letters profile →

Peers

Imen Charfi

CVPR

NEURO

AI

BE

RNMI

Wajdi Elhamzi Tunisia

T. Kalaiselvi India

Marko Barjaktarović Serbia

Anuj Bhardwaj India

Jainy Sachdeva India

Asim Munir Pakistan

Tian Lan China

Muhammad Umer Mushtaq China

Ali Pashaei France

Zaheer Ahmed Dayo China

Wajdi Elhamzi Tunisia

Imen Charfi

328 ×0.7

CVPR

348 ×1.0

NEURO

196 ×0.8

AI

30 ×0.2

BE

83 ×1.1

RNMI

Citations per year, relative to Imen Charfi Imen Charfi (= 1×) peers Wajdi Elhamzi

Countries citing papers authored by Imen Charfi

Since Specialization

Citations

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

Fields of papers citing papers by Imen Charfi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Imen Charfi

This figure shows the co-authorship network connecting the top 25 collaborators of Imen Charfi. A scholar is included among the top collaborators of Imen Charfi 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 Imen Charfi. Imen Charfi 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:

8 of 8 papers shown

1.

Ayadi, Wadhah, Wajdi Elhamzi, Imen Charfi, & Mohamed Atri. (2021). Deep CNN for Brain Tumor Classification. Neural Processing Letters. 53(1). 671–700. 247 indexed citations breakdown →

2.

Ayadi, Wadhah, Imen Charfi, Wajdi Elhamzi, & Mohamed Atri. (2020). Brain tumor classification based on hybrid approach. The Visual Computer. 38(1). 107–117. 74 indexed citations

3.

Ayadi, Wadhah, Wajdi Elhamzi, Imen Charfi, & Mohamed Atri. (2018). A hybrid feature extraction approach for brain MRI classification based on Bag-of-words. Biomedical Signal Processing and Control. 48. 144–152. 56 indexed citations

4.

Ayadi, Wadhah, et al.. (2018). Brain MRI classification using discrete wavelet transform and bag-of-words. 329. 45–49. 5 indexed citations

5.

Charfi, Imen & Mohamed Atri. (2015). Spatio-Temporal Wavelet Based Video Compression: a Simulink Implementation for Acceleration. International Review on Computers and Software (IRECOS). 10(5). 513–513. 1 indexed citations

6.

Charfi, Imen, et al.. (2014). Fast prototyping of a SoC-based smart-camera: a real-time fall detection case study. Journal of Real-Time Image Processing. 12(4). 649–662. 27 indexed citations

7.

Charfi, Imen, Johel Mitéran, Julien Dubois, Mohamed Atri, & Rached Tourki. (2013). Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification. Journal of Electronic Imaging. 22(4). 41106–41106. 116 indexed citations

8.

Charfi, Imen, Johel Mitéran, Julien Dubois, Mohamed Atri, & Rached Tourki. (2012). Definition and Performance Evaluation of a Robust SVM Based Fall Detection Solution. 218–224. 99 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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