Michael Majurski

630 total citations
19 papers, 351 citations indexed

About

Michael Majurski is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Media Technology. According to data from OpenAlex, Michael Majurski has authored 19 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Biophysics, 9 papers in Computer Vision and Pattern Recognition and 6 papers in Media Technology. Recurrent topics in Michael Majurski's work include Cell Image Analysis Techniques (11 papers), Image Processing Techniques and Applications (6 papers) and Advanced Neural Network Applications (4 papers). Michael Majurski is often cited by papers focused on Cell Image Analysis Techniques (11 papers), Image Processing Techniques and Applications (6 papers) and Advanced Neural Network Applications (4 papers). Michael Majurski collaborates with scholars based in United States, Poland and Egypt. Michael Majurski's co-authors include Joe Chalfoun, Peter Bajcsy, Kiran Bhadriraju, Mary Brady, Adele P. Peskin, Walid Keyrouz, Alden Dima, Carl G. Simon, Michael Halter and Christina H. Stuelten and has published in prestigious journals such as Scientific Reports, BMC Bioinformatics and Computer.

In The Last Decade

Michael Majurski

15 papers receiving 339 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Majurski United States	8	161	112	92	83	63	19	351
Joe Chalfoun United States	11	223 1.4×	109 1.0×	165 1.8×	100 1.2×	110 1.7×	32	468
Shenghua He United States	8	99 0.6×	80 0.7×	88 1.0×	46 0.6×	81 1.3×	25	355
Jesse Berent United Kingdom	8	60 0.4×	254 2.3×	62 0.7×	131 1.6×	71 1.1×	14	501
Marcin Kociołek Poland	9	94 0.6×	62 0.6×	41 0.4×	43 0.5×	51 0.8×	17	315
Hans Netten Netherlands	10	167 1.0×	62 0.6×	147 1.6×	115 1.4×	65 1.0×	16	389
Umesh Adiga United States	5	195 1.2×	139 1.2×	84 0.9×	60 0.7×	32 0.5×	8	338
Michael Schwarzfischer Germany	11	223 1.4×	60 0.5×	299 3.3×	69 0.8×	101 1.6×	11	511
Kenong Wu Canada	7	102 0.6×	170 1.5×	21 0.2×	51 0.6×	38 0.6×	13	297
Jane Hung United States	7	152 0.9×	59 0.5×	143 1.6×	76 0.9×	64 1.0×	8	382
Luhong Jin China	8	267 1.7×	47 0.4×	68 0.7×	90 1.1×	171 2.7×	24	436

Countries citing papers authored by Michael Majurski

Since Specialization

Citations

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

Fields of papers citing papers by Michael Majurski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Majurski

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

All Works

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19 of 19 papers shown

Majurski, Michael, et al.. (2024). A Method of Moments Embedding Constraint and its Application to Semi-Supervised Learning. 7809–7818. 1 indexed citations

Bajcsy, Peter, Nicholas J. Schaub, & Michael Majurski. (2021). Designing Trojan Detectors in Neural Networks Using Interactive Simulations. Applied Sciences. 11(4). 1865–1865. 1 indexed citations

Majurski, Michael & Peter Bajcsy. (2021). Exact Tile-Based Segmentation Inference for Images Larger than GPU Memory. Journal of Research of the National Institute of Standards and Technology. 126. 126009–126009. 1 indexed citations

Peskin, Adele P., Boris Wilthan, & Michael Majurski. (2020). Detection of Dense, Overlapping, Geometric Objects. International Journal of Artificial Intelligence & Applications. 11(4). 29–40. 2 indexed citations

Bajcsy, Peter, et al.. (2020). Approaches to training multiclass semantic image segmentation of damage in concrete. Journal of Microscopy. 279(2). 98–113. 7 indexed citations

Halter, Michael, et al.. (2020). Analyzing U-Net Robustness for Single Cell Nucleus Segmentation from Phase Contrast Images. 10 indexed citations

Majurski, Michael, Petru Manescu, Nicholas J. Schaub, et al.. (2019). Cell Image Segmentation Using Generative Adversarial Networks, Transfer Learning, and Augmentations. 1114–1122. 50 indexed citations

Peterson, Alexander W., Michael Halter, Jeffrey R. Stinson, et al.. (2018). Large field of view quantitative phase imaging of induced pluripotent stem cells and optical pathlength reference materials. s3–95. 86–86.

Chalfoun, Joe, Michael Majurski, Kiran Bhadriraju, et al.. (2017). MIST: Accurate and Scalable Microscopy Image Stitching Tool with Stage Modeling and Error Minimization. Scientific Reports. 7(1). 4988–4988. 115 indexed citations

10.

Majurski, Michael, Joe Chalfoun, Keana Scott, et al.. (2017). From Image Tiles to Web-Based Interactive Measurements in One Stop. Microscopy Today. 25(1). 18–27.

11.

Chalfoun, Joe, et al.. (2016). Lineage mapper: A versatile cell and particle tracker. Scientific Reports. 6(1). 36984–36984. 29 indexed citations

12.

Bajcsy, Peter, et al.. (2016). Enabling Stem Cell Characterization from Large Microscopy Images. Computer. 49(7). 70–79. 4 indexed citations

13.

Majurski, Michael, Joe Chalfoun, Steven P. Lund, Peter Bajcsy, & Mary Brady. (2016). Methodology for Increasing the Measurement Accuracy of Image Features. 2. 1399–1407. 1 indexed citations

14.

Bajcsy, Peter, Antonio Cardone, Joe Chalfoun, et al.. (2015). Survey statistics of automated segmentations applied to optical imaging of mammalian cells. BMC Bioinformatics. 16(1). 330–330. 35 indexed citations

15.

Majurski, Michael, et al.. (2015). From Image Tiles to Web-Based Interactive Measurements in One Stop. Microscopy and Microanalysis. 21(S3). 89–90. 1 indexed citations

16.

Chalfoun, Joe, et al.. (2015). Empirical gradient threshold technique for automated segmentation across image modalities and cell lines. Journal of Microscopy. 260(1). 86–99. 36 indexed citations

17.

Chalfoun, Joe, et al.. (2015). MIST: Microscopy Image Stitching Tool. 1757–1757. 3 indexed citations

18.

Chalfoun, Joe, et al.. (2014). Background intensity correction for terabyte‐sized time‐lapse images. Journal of Microscopy. 257(3). 226–237. 7 indexed citations

19.

Chalfoun, Joe, et al.. (2014). FogBank: a single cell segmentation across multiple cell lines and image modalities. BMC Bioinformatics. 15(1). 431–431. 48 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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