Marguerite Moore

9 total papers · 576 total citations
7 papers, 364 citations indexed

About

Marguerite Moore is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Industrial and Manufacturing Engineering. According to data from OpenAlex, Marguerite Moore has authored 7 papers receiving a total of 364 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 2 papers in Media Technology and 2 papers in Industrial and Manufacturing Engineering. Recurrent topics in Marguerite Moore's work include Advanced Image Fusion Techniques (2 papers), Industrial Vision Systems and Defect Detection (2 papers) and Image and Signal Denoising Methods (2 papers). Marguerite Moore is often cited by papers focused on Advanced Image Fusion Techniques (2 papers), Industrial Vision Systems and Defect Detection (2 papers) and Image and Signal Denoising Methods (2 papers). Marguerite Moore collaborates with scholars based in United States, India and South Korea. Marguerite Moore's co-authors include Charles Kenney, Yining Deng, B.S. Manjunath, Hyejin Shin, Samit Chakraborty, Jayanta Mukherjee, Sushmita Mitra, Glenn Washer, Daniel Saloni and Jennifer Duke and has published in prestigious journals such as IEEE Transactions on Image Processing, Sustainability and International Journal of Fashion Design Technology and Education.

In The Last Decade

Marguerite Moore

6 papers receiving 329 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Marguerite Moore	297	85	27	19	19	7	364
Khamar Basha Shaik	160 0.5×	58 0.7×	14 0.5×	44 2.3×	11 0.6×	6	328
Hideo Fukamachi	307 1.0×	39 0.5×	40 1.5×	36 1.9×	10 0.5×	11	361
Alexandru Drîmbărean	193 0.6×	81 1.0×	31 1.1×	31 1.6×	8 0.4×	15	299
J. Föglein	195 0.7×	81 1.0×	20 0.7×	53 2.8×	14 0.7×	8	323
Ralf R. Kohler	221 0.7×	63 0.7×	9 0.3×	40 2.1×	5 0.3×	6	311
Hossein Ziaei Nafchi	284 1.0×	162 1.9×	7 0.3×	25 1.3×	13 0.7×	13	346
Azriel Rosenfeld	305 1.0×	90 1.1×	16 0.6×	38 2.0×	8 0.4×	8	397
Sen Jia	175 0.6×	48 0.6×	42 1.6×	47 2.5×	5 0.3×	10	298
Sing‐Tze Bow	225 0.8×	33 0.4×	43 1.6×	79 4.2×	13 0.7×	7	394
Ajay Kumar Boyat	201 0.7×	111 1.3×	27 1.0×	43 2.3×	4 0.2×	8	315

Countries citing papers authored by Marguerite Moore

Since Specialization

Citations

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

Fields of papers citing papers by Marguerite Moore

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marguerite Moore

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

All Works

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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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