Gil Sadeh

631 total citations
2 papers, 179 citations indexed

About

Gil Sadeh is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases. According to data from OpenAlex, Gil Sadeh has authored 2 papers receiving a total of 179 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Computer Vision and Pattern Recognition, 1 paper in Artificial Intelligence and 0 papers in Infectious Diseases. Recurrent topics in Gil Sadeh's work include Advanced Image and Video Retrieval Techniques (1 paper), Image Retrieval and Classification Techniques (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). Gil Sadeh is often cited by papers focused on Advanced Image and Video Retrieval Techniques (1 paper), Image Retrieval and Classification Techniques (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). Gil Sadeh collaborates with scholars based in Israel and France. Gil Sadeh's co-authors include Lior Wolf, Guy Lev, Benjamin Klein, Nachum Dershowitz, Tal Hassner and Daniel Stökl Ben Ezra and has published in prestigious journals such as .

In The Last Decade

Gil Sadeh

2 papers receiving 175 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gil Sadeh Israel	2	170	95	4	3	1	2	179
Guy Lev United States	3	168 1.0×	107 1.1×	4 1.0×	4 1.3×	1 1.0×	5	192
Volkan Cirik United States	6	139 0.8×	150 1.6×		2 0.7×	1 1.0×	9	180
Yutaro Shigeto Japan	4	71 0.4×	67 0.7×		2 0.7×		10	100
Robik Shrestha United States	6	102 0.6×	98 1.0×		3 1.0×		7	126
Zarana Parekh United States	5	77 0.5×	55 0.6×		4 1.3×		6	103
Jyoti Aneja United States	3	98 0.6×	53 0.6×		1 0.3×		4	112
Zaixiang Zheng China	7	99 0.6×	164 1.7×		5 1.7×	2 2.0×	10	176
Eva Giboulot France	7	151 0.9×	24 0.3×		4 1.3×	2 2.0×	9	153
Umapada Pal India	7	129 0.8×	31 0.3×		2 0.7×		12	134
Rosanne Liu United States	3	82 0.5×	73 0.8×		1 0.3×	2 2.0×	5	121

Countries citing papers authored by Gil Sadeh

Since Specialization

Citations

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

Fields of papers citing papers by Gil Sadeh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gil Sadeh

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

All Works

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2 of 2 papers shown

1.

Sadeh, Gil, Lior Wolf, Tal Hassner, Nachum Dershowitz, & Daniel Stökl Ben Ezra. (2015). Viral transcript alignment. 711–715. 3 indexed citations

2.

Klein, Benjamin, Guy Lev, Gil Sadeh, & Lior Wolf. (2015). Associating neural word embeddings with deep image representations using Fisher Vectors. 4437–4446. 176 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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