Elnaz Barshan

448 total citations
7 papers, 235 citations indexed

About

Elnaz Barshan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Elnaz Barshan has authored 7 papers receiving a total of 235 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Media Technology. Recurrent topics in Elnaz Barshan's work include Generative Adversarial Networks and Image Synthesis (2 papers), Advanced Neural Network Applications (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Elnaz Barshan is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (2 papers), Advanced Neural Network Applications (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Elnaz Barshan collaborates with scholars based in Canada, Germany and United Kingdom. Elnaz Barshan's co-authors include Mansoor Zolghadri Jahromi, Ali Ghodsi, Zohreh Azimifar, Paul Fieguth, Gintare Karolina Dziugaite, Christian Scharfenberger, Alexander Wong, Xiyang Luo, Feng Yang and Michael E. Goebel and has published in prestigious journals such as Pattern Recognition, Neural Information Processing Systems and International Conference on Artificial Intelligence and Statistics.

In The Last Decade

Elnaz Barshan

7 papers receiving 227 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Elnaz Barshan Canada	5	92	87	25	25	23	7	235
Euisun Choi South Korea	7	170 1.8×	88 1.0×	20 0.8×	27 1.1×	47 2.0×	23	356
Olga Kouropteva Finland	4	125 1.4×	67 0.8×	13 0.5×	13 0.5×	32 1.4×	5	200
Srikumar Sastry United States	4	74 0.8×	42 0.5×	12 0.5×	9 0.4×	27 1.2×	13	203
Douglas R. Heisterkamp United States	10	226 2.5×	136 1.6×	17 0.7×	12 0.5×	29 1.3×	26	334
Alexandre L. M. Levada Brazil	9	109 1.2×	48 0.6×	8 0.3×	12 0.5×	39 1.7×	52	244
Kerstin Malmqvist Sweden	9	119 1.3×	140 1.6×	7 0.3×	20 0.8×	28 1.2×	29	299
Zilan Hu China	7	229 2.5×	101 1.2×	10 0.4×	27 1.1×	37 1.6×	10	293
Li-Lun Wang United States	5	151 1.6×	142 1.6×	14 0.6×	8 0.3×	17 0.7×	7	284
Songcan Chen China	9	215 2.3×	138 1.6×	7 0.3×	14 0.6×	42 1.8×	15	305

Countries citing papers authored by Elnaz Barshan

Since Specialization

Citations

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

Fields of papers citing papers by Elnaz Barshan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elnaz Barshan

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

All Works

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7 of 7 papers shown

1.

Luo, Xiyang, Michael E. Goebel, Elnaz Barshan, & Feng Yang. (2023). LECA: A learned approach for efficient cover-agnostic watermarking. Electronic Imaging. 35(4). 376–1. 4 indexed citations

2.

Barshan, Elnaz, et al.. (2020). RelatIF: Identifying Explanatory Training Samples via Relative Influence. International Conference on Artificial Intelligence and Statistics. 1899–1909. 10 indexed citations

3.

Barshan, Elnaz & Paul Fieguth. (2015). Stage-wise Training: An Improved Feature Learning Strategy for Deep Models. Neural Information Processing Systems. 49–59. 11 indexed citations

4.

Barshan, Elnaz, et al.. (2015). 35.3: Resolution Enhancement Based on Shifted Superposition. SID Symposium Digest of Technical Papers. 46(1). 514–517. 6 indexed citations

5.

Barshan, Elnaz, Paul Fieguth, & Alexander Wong. (2015). Scalable multi-neighborhood learning for convolutional networks. 1–6. 2 indexed citations

6.

Barshan, Elnaz & Paul Fieguth. (2014). Scalable learning for restricted Boltzmann machines. 1. 2754–2758. 1 indexed citations

7.

Barshan, Elnaz, Ali Ghodsi, Zohreh Azimifar, & Mansoor Zolghadri Jahromi. (2010). Supervised principal component analysis: Visualization, classification and regression on subspaces and submanifolds. Pattern Recognition. 44(7). 1357–1371. 201 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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