Nibal Nayef

772 total citations
9 papers, 63 citations indexed

About

Nibal Nayef is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Communication. According to data from OpenAlex, Nibal Nayef has authored 9 papers receiving a total of 63 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 2 papers in Media Technology and 1 paper in Communication. Recurrent topics in Nibal Nayef's work include Handwritten Text Recognition Techniques (6 papers), Image Retrieval and Classification Techniques (4 papers) and Image Processing and 3D Reconstruction (4 papers). Nibal Nayef is often cited by papers focused on Handwritten Text Recognition Techniques (6 papers), Image Retrieval and Classification Techniques (4 papers) and Image Processing and 3D Reconstruction (4 papers). Nibal Nayef collaborates with scholars based in Germany, France and Palestinian Territory. Nibal Nayef's co-authors include Thomas M. Breuel, Aziz Qaroush, Imen Bizid, Antoine Doucet, Muriel Visani and Jean-Marc Ogier and has published in prestigious journals such as Information Systems, Journal of King Saud University - Computer and Information Sciences and HAL (Le Centre pour la Communication Scientifique Directe).

In The Last Decade

Nibal Nayef

9 papers receiving 62 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nibal Nayef Germany	6	47	13	10	9	8	9	63
Mostafa S. Ibrahim Egypt	2	57 1.2×	13 1.0×	30 3.0×	1 0.1×	6 0.8×	2	77
J. Kahn Germany	5	11 0.2×	5 0.4×	10 1.0×	7 0.8×	2 0.3×	11	51
Taeyoung Son South Korea	3	58 1.2×	10 0.8×	25 2.5×		3 0.4×	3	69
Lala Li United States	4	42 0.9×	4 0.3×	15 1.5×		2 0.3×	8	66
A. Kamenev Australia	2	56 1.2×	16 1.2×	3 0.3×	1 0.1×	3 0.4×	2	66
Mohamed Zahran Egypt	2	40 0.9×	3 0.2×	5 0.5×	2 0.2×	3 0.4×	7	48
Florian Chabot France	4	60 1.3×	5 0.4×	17 1.7×		3 0.4×	9	67
Abdullah Hamdi Saudi Arabia	5	38 0.8×	2 0.2×	9 0.9×	10 1.1×	1 0.1×	10	66
Adam Stambler United States	4	10 0.2×	3 0.2×	8 0.8×	11 1.2×		7	33
Chu-Tak Li Hong Kong	3	35 0.7×	14 1.1×	3 0.3×	3 0.3×		6	41

Countries citing papers authored by Nibal Nayef

Since Specialization

Citations

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

Fields of papers citing papers by Nibal Nayef

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nibal Nayef

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

All Works

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9 of 9 papers shown

1.

Qaroush, Aziz, et al.. (2019). An efficient, font independent word and character segmentation algorithm for printed Arabic text. Journal of King Saud University - Computer and Information Sciences. 34(1). 1330–1344. 19 indexed citations

2.

Bizid, Imen, et al.. (2017). Detecting prominent microblog users over crisis events phases. Information Systems. 78. 173–188. 7 indexed citations

3.

Nayef, Nibal, et al.. (2015). Metric-based no-reference quality assessment of heterogeneous document images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9402. 94020L–94020L. 8 indexed citations

4.

Nayef, Nibal, et al.. (2014). Document Retrieval Based on Logo Spotting Using Key-Point Matching. HAL (Le Centre pour la Communication Scientifique Directe). 3056–3061. 1 indexed citations

5.

Nayef, Nibal & Thomas M. Breuel. (2013). Efficient symbol retrieval by building a symbol index from a collection of line drawings. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8658. 86580Y–86580Y. 3 indexed citations

6.

Nayef, Nibal & Thomas M. Breuel. (2013). Combining geometric matching with SVM to improve symbol spotting. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8658. 86580G–86580G. 3 indexed citations

7.

Nayef, Nibal. (2013). Geometric-based Symbol Spotting and Retrieval in Technical Line Drawings. Publication Server of Kaiserslautern University of Technology (Kaiserslautern University of Technology). 5 indexed citations

8.

Nayef, Nibal & Thomas M. Breuel. (2011). Statistical Grouping for Segmenting Symbols Parts from Line Drawings, with Application to Symbol Spotting. 364–368. 10 indexed citations

9.

Nayef, Nibal & Thomas M. Breuel. (2010). Graphical symbol retrieval using a branch and bound algorithm. 9. 2153–2156. 7 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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