Akrem Sellami

755 total citations
18 papers, 562 citations indexed

About

Akrem Sellami is a scholar working on Media Technology, Atmospheric Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Akrem Sellami has authored 18 papers receiving a total of 562 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Media Technology, 11 papers in Atmospheric Science and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Akrem Sellami's work include Remote-Sensing Image Classification (12 papers), Remote Sensing and Land Use (11 papers) and Advanced Image Fusion Techniques (9 papers). Akrem Sellami is often cited by papers focused on Remote-Sensing Image Classification (12 papers), Remote Sensing and Land Use (11 papers) and Advanced Image Fusion Techniques (9 papers). Akrem Sellami collaborates with scholars based in France, Tunisia and China. Akrem Sellami's co-authors include Salvatore Tabbone, Imed Riadh Farah, Mohamed Farah, Basel Solaiman, Boubakr Nour, Senlin Luo, Hakima Khelifi, Hassine Moungla, Ali Ben Abbes and Vincent Barra and has published in prestigious journals such as Expert Systems with Applications, Pattern Recognition and Knowledge-Based Systems.

In The Last Decade

Akrem Sellami

16 papers receiving 548 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Akrem Sellami France 11 316 205 136 116 90 18 562
Xianfeng Ou China 16 389 1.2× 215 1.0× 236 1.7× 38 0.3× 117 1.3× 39 678
Raúl Guerra Spain 16 335 1.1× 111 0.5× 229 1.7× 25 0.2× 94 1.0× 43 644
Xiang Tan China 9 208 0.7× 116 0.6× 64 0.5× 58 0.5× 55 0.6× 15 388
Emmanuel Arzuaga Puerto Rico 6 189 0.6× 119 0.6× 82 0.6× 74 0.6× 34 0.4× 23 348
Mohsin Ali Pakistan 8 174 0.6× 106 0.5× 65 0.5× 43 0.4× 25 0.3× 15 309
Leiquan Wang China 15 235 0.7× 114 0.6× 326 2.4× 35 0.3× 186 2.1× 69 704
Fang He China 12 289 0.9× 142 0.7× 214 1.6× 20 0.2× 161 1.8× 33 558
Manoj Kumar Singh India 11 132 0.4× 67 0.3× 87 0.6× 20 0.2× 98 1.1× 39 395
Seyyid Ahmed Medjahed Algeria 7 113 0.4× 66 0.3× 97 0.7× 25 0.2× 175 1.9× 16 421
Haixia Xu China 12 105 0.3× 50 0.2× 166 1.2× 69 0.6× 87 1.0× 52 473

Countries citing papers authored by Akrem Sellami

Since Specialization
Citations

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

Fields of papers citing papers by Akrem Sellami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akrem Sellami

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

All Works

18 of 18 papers shown
1.
Sellami, Akrem, et al.. (2024). Attention-driven multi-feature fusion for hyperspectral image classification via multi-criteria optimization and multi-view convolutional neural networks. Engineering Applications of Artificial Intelligence. 138. 109434–109434.
2.
Sellami, Akrem, et al.. (2024). Graph feature fusion driven by deep autoencoder for advanced hyperspectral image unmixing. Knowledge-Based Systems. 299. 112087–112087. 4 indexed citations
3.
4.
Sellami, Akrem, et al.. (2023). Multi-view graph representation learning for hyperspectral image classification with spectral–spatial graph neural networks. Neural Computing and Applications. 36(7). 3737–3759. 13 indexed citations
5.
Sellami, Akrem, Mohamed Farah, & Mauro Dalla Mura. (2022). SHCNet: A semi-supervised hypergraph convolutional networks based on relevant feature selection for hyperspectral image classification. Pattern Recognition Letters. 165. 98–106. 19 indexed citations
6.
Sellami, Akrem, et al.. (2022). A deep learning approach based on morphological profiles for Hyperspectral Image unmixing. SPIRE - Sciences Po Institutional REpository. 1–6. 3 indexed citations
7.
Sellami, Akrem & Salvatore Tabbone. (2021). Deep neural networks-based relevant latent representation learning for hyperspectral image classification. Pattern Recognition. 121. 108224–108224. 141 indexed citations
8.
Sellami, Akrem, et al.. (2021). Semi-supervised Classification of Hyperspectral Image through Deep Encoder-Decoder and Graph Neural Networks. HAL (Le Centre pour la Communication Scientifique Directe). 12 indexed citations
9.
Sellami, Akrem & Salvatore Tabbone. (2021). Video semantic segmentation using deep multi-view representation learning. 1–7. 4 indexed citations
10.
11.
Sellami, Akrem, et al.. (2020). Mapping individual differences in cortical architecture using multi-view\n representation learning. arXiv (Cornell University). 6 indexed citations
12.
Sellami, Akrem, Ali Ben Abbes, Vincent Barra, & Imed Riadh Farah. (2020). Fused 3-D spectral-spatial deep neural networks and spectral clustering for hyperspectral image classification. Pattern Recognition Letters. 138. 594–600. 59 indexed citations
13.
Sellami, Akrem & Imed Riadh Farah. (2019). Spectra-spatial Graph-based Deep Restricted Boltzmann Networks for Hyperspectral Image Classification. 1055–1062. 13 indexed citations
14.
Sellami, Akrem, Mohamed Farah, Imed Riadh Farah, & Basel Solaiman. (2019). Hyperspectral imagery classification based on semi-supervised 3-D deep neural network and adaptive band selection. Expert Systems with Applications. 129. 246–259. 109 indexed citations
15.
Khelifi, Hakima, Senlin Luo, Boubakr Nour, et al.. (2018). Bringing Deep Learning at the Edge of Information-Centric Internet of Things. IEEE Communications Letters. 23(1). 52–55. 88 indexed citations
16.
Sellami, Akrem, Mohamed Farah, Imed Riadh Farah, & Basel Solaiman. (2018). Hyperspectral Imagery Semantic Interpretation Based on Adaptive Constrained Band Selection and Knowledge Extraction Techniques. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(4). 1337–1347. 23 indexed citations
17.
Khelifi, Hakima, et al.. (2018). An Optimized Proactive Caching Scheme Based on Mobility Prediction for Vehicular Networks. HAL (Le Centre pour la Communication Scientifique Directe). 49 indexed citations
18.
Sellami, Akrem & Imed Riadh Farah. (2016). High-level hyperspectral image classification based on spectro-spatial dimensionality reduction. Spatial Statistics. 16. 103–117. 15 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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