Roland Wilson

35 papers receiving 408 citations

Peers

Roland Wilson
Comparison fields: 5 of 79
  • Computer Vision and Pattern Recognition 291
  • Artificial Intelligence 110
  • Radiology, Nuclear Medicine and Imaging 103
  • Ophthalmology 67
  • Signal Processing 67
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Citations per field
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Citations per year

Countries citing papers authored by Roland Wilson

Since Specialization
Citations

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

Fields of papers citing papers by Roland Wilson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roland Wilson

This figure shows the co-authorship network connecting the top 25 collaborators of Roland Wilson. A scholar is included among the top collaborators of Roland Wilson 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 Roland Wilson. Roland Wilson 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 2
2
Multi-frame scene-flow estimation using a patch model and smooth motion prior
5
3 17
4 37
5 75
6 3
7 10
8
Comparative analysis of discriminant wavelet packet features and raw image features for classification of meningioma subtypes
10
9 27
10
Bayesian analysis of vascular structure
1
11
A Neural Network for Triad Classification
2
12
Feature extraction for very low bit rate video coding
0
13 9
14
A multiresolution stereopsis algorithm based on the Gabor representation
18
15 22
16 68
17
The Uncertainty Principle in Image Coding
3
18
The Uncertainty Principle in Vision
2
19
The Operational Definition of the Position of Line and Edge
7
20
Anisotropic Filtering Operations for Image Enhancement and their Relation to the Visual System
3

About Roland Wilson

Roland Wilson is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Signal Processing, having authored 36 papers that have together received 453 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (10 papers), Advanced Vision and Imaging (10 papers) and Medical Image Segmentation Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (291 citations), Ophthalmology (67 citations) and Signal Processing (67 citations). Roland Wilson has collaborated with scholars based in United Kingdom, Sweden and United States. Frequent co-authors include Goesta H. Granlund, Abhir Bhalerao, M. Spann, Li Wang, Chang‐Tsun Li, Nasir Rajpoot, Hans Knutsson, Yinyin Yuan, Hammad Qureshi and Metin N. Gürcan. Their work appears in journals such as Bioinformatics, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Medical Imaging.

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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