Todd M. Bacastow

15 total papers · 580 total citations
8 papers, 144 citations indexed

About

Todd M. Bacastow is a scholar working on Artificial Intelligence, Media Technology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Todd M. Bacastow has authored 8 papers receiving a total of 144 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 3 papers in Media Technology and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Todd M. Bacastow's work include Remote-Sensing Image Classification (3 papers), Anomaly Detection Techniques and Applications (2 papers) and Flood Risk Assessment and Management (2 papers). Todd M. Bacastow is often cited by papers focused on Remote-Sensing Image Classification (3 papers), Anomaly Detection Techniques and Applications (2 papers) and Flood Risk Assessment and Management (2 papers). Todd M. Bacastow collaborates with scholars based in United States and Germany. Todd M. Bacastow's co-authors include Ronny Hänsch, Jason Brown, Ryan Lewis, Jacob Shermeyer, Scott Soenen, David B. Hogan, N. Weir, Adam Van Etten, Fabio Pacifici and Donna J. Peuquet and has published in prestigious journals such as Journal of Government Information, International Journal of Geographical Information Systems and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

In The Last Decade

Todd M. Bacastow

7 papers receiving 139 citations

Author Peers

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

Author						Papers	Cites
Todd M. Bacastow	67	56	38	34	25	8	144
Ryan Lewis	75 1.1×	96 1.7×	62 1.6×	38 1.1×	33 1.3×	5	273
Adam Van Etten	77 1.1×	98 1.8×	63 1.7×	38 1.1×	36 1.4×	4	187
Man Zhang	67 1.0×	142 2.5×	59 1.6×	31 0.9×	32 1.3×	7	289
Ryuhei Hamaguchi	99 1.5×	66 1.2×	26 0.7×	33 1.0×	30 1.2×	14	195
Zhuoyi Zhao	99 1.5×	45 0.8×	39 1.0×	17 0.5×	20 0.8×	16	217
Junghoon Seo	50 0.7×	59 1.1×	20 0.5×	10 0.3×	31 1.2×	7	117
Zhujun Yang	147 2.2×	125 2.2×	51 1.3×	36 1.1×	63 2.5×	11	288
Peng Zhang	108 1.6×	112 2.0×	45 1.2×	27 0.8×	23 0.9×	14	245
Ritwik Gupta	115 1.7×	81 1.4×	20 0.5×	35 1.0×	59 2.4×	7	255
Eric Heim	66 1.0×	80 1.4×	21 0.6×	18 0.5×	48 1.9×	10	227

Countries citing papers authored by Todd M. Bacastow

Since Specialization

Citations

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

Fields of papers citing papers by Todd M. Bacastow

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Todd M. Bacastow. 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 Todd M. Bacastow. The network helps show where Todd M. Bacastow may publish in the future.

Co-authorship network of co-authors of Todd M. Bacastow

This figure shows the co-authorship network connecting the top 25 collaborators of Todd M. Bacastow. A scholar is included among the top collaborators of Todd M. Bacastow 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 Todd M. Bacastow. Todd M. Bacastow 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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