Alice Porebski

449 total citations
19 papers, 156 citations indexed

About

Alice Porebski is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Analytical Chemistry. According to data from OpenAlex, Alice Porebski has authored 19 papers receiving a total of 156 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 9 papers in Media Technology and 3 papers in Analytical Chemistry. Recurrent topics in Alice Porebski's work include Image Retrieval and Classification Techniques (16 papers), Advanced Image and Video Retrieval Techniques (12 papers) and Remote-Sensing Image Classification (9 papers). Alice Porebski is often cited by papers focused on Image Retrieval and Classification Techniques (16 papers), Advanced Image and Video Retrieval Techniques (12 papers) and Remote-Sensing Image Classification (9 papers). Alice Porebski collaborates with scholars based in France, Morocco and Lebanon. Alice Porebski's co-authors include Nicolas Vandenbroucke, Ludovic Macaire, Denis Hamad, Vinh Truong Hoang, Olivier Losson, Sanaa El Fkihi, Rachid Amara, Périne Doyen and Rachid Oulad Haj Thami and has published in prestigious journals such as Marine Pollution Bulletin, Pattern Recognition and Remote Sensing.

In The Last Decade

Alice Porebski

18 papers receiving 143 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alice Porebski France 8 102 48 22 18 12 19 156
Nicolas Vandenbroucke France 9 194 1.9× 86 1.8× 33 1.5× 34 1.9× 13 1.1× 28 290
Hongyu Chen China 9 122 1.2× 119 2.5× 37 1.7× 3 0.2× 14 1.2× 26 286
D. Camarero Munoz Switzerland 4 68 0.7× 28 0.6× 4 0.2× 3 0.2× 32 2.7× 6 137
B. Sathya Bama India 7 52 0.5× 59 1.2× 10 0.5× 41 2.3× 20 181
Xiaotong Luo China 7 100 1.0× 45 0.9× 9 0.4× 1 0.1× 17 1.4× 21 149
Ranjan Mondal India 7 146 1.4× 132 2.8× 19 0.9× 13 0.7× 9 226
Ali Soltani-Farani Iran 5 68 0.7× 131 2.7× 11 0.5× 11 0.6× 2 0.2× 8 163
Jingbing Li China 7 206 2.0× 32 0.7× 24 1.1× 2 0.1× 15 236
Ankur Garg India 5 58 0.6× 122 2.5× 15 0.7× 10 0.6× 13 169
Xiaoyu Yue China 6 79 0.8× 23 0.5× 30 1.4× 2 0.1× 7 97

Countries citing papers authored by Alice Porebski

Since Specialization
Citations

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

Fields of papers citing papers by Alice Porebski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alice Porebski

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

All Works

19 of 19 papers shown
1.
Porebski, Alice, et al.. (2025). Hyperspectral space transformations for texture classification. Pattern Recognition. 172. 112335–112335.
2.
Porebski, Alice, et al.. (2025). A lightweight spatial and spectral CNN model for classifying floating marine plastic debris using hyperspectral images. Marine Pollution Bulletin. 216. 117965–117965. 3 indexed citations
3.
4.
Porebski, Alice, et al.. (2023). An Order and Difference Local Binary Pattern for Hyperspectral Texture Classification. SPIRE - Sciences Po Institutional REpository. 1–6. 1 indexed citations
5.
Porebski, Alice, et al.. (2022). Compact Hybrid Multi-Color Space Descriptor Using Clustering-Based Feature Selection for Texture Classification. Journal of Imaging. 8(8). 217–217. 5 indexed citations
6.
Porebski, Alice, et al.. (2022). Comparison of color imaging vs. hyperspectral imaging for texture classification. Pattern Recognition Letters. 161. 115–121. 10 indexed citations
7.
Porebski, Alice, et al.. (2021). Clustering-based Sequential Feature Selection Approach for High Dimensional Data Classification. SPIRE - Sciences Po Institutional REpository. 122–132. 5 indexed citations
8.
Porebski, Alice, Vinh Truong Hoang, Nicolas Vandenbroucke, & Denis Hamad. (2020). Combination of LBP Bin and Histogram Selections for Color Texture Classification. Journal of Imaging. 6(6). 53–53. 11 indexed citations
9.
Vandenbroucke, Nicolas, et al.. (2019). Compact Color Texture Representation by Feature Selection in Multiple Color Spaces. 436–443. 2 indexed citations
10.
Vandenbroucke, Nicolas, et al.. (2019). Compact Color Texture Representation by Feature Selection in Multiple Color Spaces. HAL (Le Centre pour la Communication Scientifique Directe). 436–443. 1 indexed citations
11.
Porebski, Alice, et al.. (2018). Unsupervised Local Binary Pattern Histogram Selection Scores for Color Texture Classification. Journal of Imaging. 4(10). 112–112. 7 indexed citations
12.
Porebski, Alice & Vinh Truong Hoang. (2018). Multi-color space local binary pattern-based feature selection for texture classification. Journal of Electronic Imaging. 27(1). 1–1. 15 indexed citations
13.
Hoang, Vinh Truong, Alice Porebski, Nicolas Vandenbroucke, & Denis Hamad. (2017). LBP Histogram Selection based on Sparse Representation for Color Texture Classification. HAL (Le Centre pour la Communication Scientifique Directe). 8 indexed citations
14.
Porebski, Alice, Nicolas Vandenbroucke, Ludovic Macaire, & Denis Hamad. (2013). A new benchmark image test suite for evaluating colour texture classification schemes. Multimedia Tools and Applications. 70(1). 543–556. 23 indexed citations
15.
Losson, Olivier, Alice Porebski, Nicolas Vandenbroucke, & Ludovic Macaire. (2013). Color texture analysis using CFA chromatic co-occurrence matrices. Computer Vision and Image Understanding. 117(7). 747–763. 17 indexed citations
16.
Porebski, Alice, Nicolas Vandenbroucke, & Ludovic Macaire. (2012). Supervised texture classification: color space or texture feature selection?. Pattern Analysis and Applications. 26 indexed citations
17.
Porebski, Alice, et al.. (2010). Constraint score for semi-supervised selection of color texture features. 275–279. 1 indexed citations
18.
Porebski, Alice, Nicolas Vandenbroucke, & Ludovic Macaire. (2010). A multi color space approach for texture classification: experiments with Outex, Vistex and Barktex image databases. Conference on Colour in Graphics Imaging and Vision. 5(1). 314–319. 1 indexed citations
19.
Porebski, Alice, Nicolas Vandenbroucke, & Ludovic Macaire. (2008). Neighborhood and Haralick feature extraction for color texture analysis. Conference on Colour in Graphics Imaging and Vision. 4(1). 316–321. 5 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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