Eric Heim

606 total citations
10 papers, 228 citations indexed

About

Eric Heim is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Science Applications. According to data from OpenAlex, Eric Heim has authored 10 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 3 papers in Computer Science Applications. Recurrent topics in Eric Heim's work include Mobile Crowdsensing and Crowdsourcing (3 papers), Advanced Neural Network Applications (2 papers) and Augmented Reality Applications (2 papers). Eric Heim is often cited by papers focused on Mobile Crowdsensing and Crowdsourcing (3 papers), Advanced Neural Network Applications (2 papers) and Augmented Reality Applications (2 papers). Eric Heim collaborates with scholars based in Germany, United States and Switzerland. Eric Heim's co-authors include Nirav Patel, Bryce Goodman, Matthew E. Gaston, Ritwik Gupta, Jigar Doshi, Howie Choset, Alexander Seitel, Lena Maier‐Hein, Tobias Roß and Keno März and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Assisted Radiology and Surgery and Journal of Medical Imaging.

In The Last Decade

Eric Heim

9 papers receiving 226 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eric Heim Germany	5	81	66	49	39	28	10	228
Shubham Innani United States	4	132 1.6×	34 0.5×	72 1.5×	55 1.4×	19 0.7×	15	295
Jiawen Lin China	10	102 1.3×	108 1.6×	53 1.1×	70 1.8×	21 0.8×	50	506
Tianyun Zhao China	7	147 1.8×	157 2.4×	51 1.0×	34 0.9×	37 1.3×	29	371
Lars Aurdal Norway	9	103 1.3×	58 0.9×	16 0.3×	39 1.0×	17 0.6×	23	332
Paramate Horkaew Thailand	11	80 1.0×	21 0.3×	50 1.0×	30 0.8×	117 4.2×	48	367
Haeyun Lee South Korea	8	94 1.2×	83 1.3×	146 3.0×	113 2.9×	11 0.4×	15	328
Bin Tian China	9	70 0.9×	77 1.2×	84 1.7×	64 1.6×	27 1.0×	25	289
Yanfeng Shang China	10	182 2.2×	125 1.9×	67 1.4×	77 2.0×	13 0.5×	24	352
Hatice Çatal Reis Türkiye	10	61 0.8×	18 0.3×	111 2.3×	47 1.2×	33 1.2×	33	406

Countries citing papers authored by Eric Heim

Since Specialization

Citations

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

Fields of papers citing papers by Eric Heim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Heim

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

Heim, Eric, et al.. (2019). Exploiting Class Learnability in Noisy Data. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 4082–4089. 2 indexed citations

Gupta, Ritwik, Bryce Goodman, Nirav Patel, et al.. (2019). Creating xBD: A Dataset for Assessing Building Damage from Satellite Imagery. Figshare. 10–17. 107 indexed citations

Heim, Eric, Tobias Roß, Alexander Seitel, et al.. (2018). Large-scale medical image annotation with crowd-powered algorithms. Journal of Medical Imaging. 5(3). 1–1. 34 indexed citations

Heim, Eric, Alexander Seitel, Fabian Isensee, et al.. (2017). Clickstream Analysis for Crowd-Based Object Segmentation with Confidence. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(12). 2814–2826. 8 indexed citations

Franz, Alfred M., et al.. (2016). Structure Sensor for mobile markerless augmented reality. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9786. 97861L–97861L. 1 indexed citations

Goetz, Michael, Eric Heim, Tobias Norajitra, et al.. (2016). A learning-based, fully automatic liver tumor segmentation pipeline based on sparsely annotated training data. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 2 indexed citations

Heim, Eric & Miloš Hauskrecht. (2015). Sparse multidimensional patient modeling using auxiliary confidence labels. PubMed. 2015. 331–336. 1 indexed citations

Maier‐Hein, Lena, Daniel Kondermann, Tobias Roß, et al.. (2015). Crowdtruth validation: a new paradigm for validating algorithms that rely on image correspondences. International Journal of Computer Assisted Radiology and Surgery. 10(8). 1201–1212. 20 indexed citations

Heim, Eric, Sven Haase, Michael Müller, et al.. (2014). Mobile markerless augmented reality and its application in forensic medicine. International Journal of Computer Assisted Radiology and Surgery. 10(5). 573–586. 53 indexed citations

10.

Heim, Eric, et al.. (1988). Development of a versatile rotation transformation algorithm for automatic model attitude positioning. 26th Aerospace Sciences Meeting.

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.

Explore authors with similar magnitude of impact