Matthew B. Blaschko

75 papers receiving 3.3k citations

Hit Papers

The Lovasz-Softmax Loss: A Tractable ...20082026201420202018200820162020100200300400500

Peers

Matthew B. Blaschko
Comparison fields: 5 of 148
  • Computer Vision and Pattern Recognition 2.2k
  • Radiology, Nuclear Medicine and Imaging 957
  • Artificial Intelligence 710
  • Ophthalmology 597
  • Aerospace Engineering 314
Replace Xin Yang with:
Xin Yang China
Mai Xu China
Xinge You China
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Manoranjan Paul Australia
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Karel J. Zuiderveld Netherlands
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Matthew B. Blaschko relative to Xin Yang China Xin Yang's profile →
Citations per field
00.5×3.3×
Xin Yang · 1×
Citations per year

Countries citing papers authored by Matthew B. Blaschko

Since Specialization
Citations

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

Fields of papers citing papers by Matthew B. Blaschko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew B. Blaschko. 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 Matthew B. Blaschko. The network helps show where Matthew B. Blaschko may publish in the future.

Co-authorship network of co-authors of Matthew B. Blaschko

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 4
3 0
4 39
5 19
6 6
7 6
8
Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Indexbreakdown →
250
9 37
10 4
11 78
12 14
13 40
14
Stochastic Weighted Function Norm Regularization.
1
15
B-test: A Non-parametric, Low Variance Kernel Two-sample Test
18
16 2
17
Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity
4
18
Learning to Localize Objects with Structured Output Regression
2
19 1
20
A multiple kernel learning approach to joint multi-class object detection
6

About Matthew B. Blaschko

Matthew B. Blaschko is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Ophthalmology, having authored 81 papers that have together received 3.4k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (14 papers), Face and Expression Recognition (11 papers) and Domain Adaptation and Few-Shot Learning (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.2k citations), Ophthalmology (597 citations) and Radiology, Nuclear Medicine and Imaging (957 citations). Matthew B. Blaschko has collaborated with scholars based in Belgium, Germany and France. Frequent co-authors include Christoph H. Lampert, Thomas Hofmann, Maxim Berman, José Ignacio Orlando, Amal Rannen Triki, Elena Prokofyeva, Esa Rahtu, Juho Kannala, Frederik Maes and Tom Eelbode. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and IEEE Transactions on Biomedical Engineering.

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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