Jacob Scharcanski

2.9k citations
116 papers · 2.1k · h-index 26

Impact in

Papers in

Jacob Scharcanski

111 papers receiving 1.9k citations

Peers

Jacob Scharcanski
Comparison fields: 5 of 130
  • Computer Vision and Pattern Recognition 1.1k
  • Ophthalmology 304
  • Media Technology 253
  • Radiology, Nuclear Medicine and Imaging 456
  • Oncology 432
Replace Steven Lawrence Fernandes with:
Steven Lawrence Fernandes India
Mudassar Raza Pakistan
Valery Naranjo Spain
Deepak Ranjan Nayak India
Xieping Gao China
Javaria Amin Pakistan
Naoufel Werghi United Arab Emirates
Yanwu Xu China
Costantino Grana Italy
Şaban Öztürk Türkiye
Jacob Scharcanski relative to Steven Lawrence Fernandes India Steven Lawrence Fernandes's profile →
Citations per field
00.5×6.3×
Steven Lawrence Fernandes · 1×
Citations per year

Countries citing papers authored by Jacob Scharcanski

Since Specialization
Citations

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

Fields of papers citing papers by Jacob Scharcanski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jacob Scharcanski, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jacob Scharcanski Line = papers co-authored together Jacob Scharcanski links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 116 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010132
2 2009125
3 2011117
4 2011108
5 201687
6 201372
7 201065
8 199760
9 201259
10 201354
11 201651
12 200546
13 200644
14 201044
15 201443
16 201339
17 200237
18 201536
19 201836
20 201334

About Jacob Scharcanski

Jacob Scharcanski is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Oncology and Industrial and Manufacturing Engineering, having authored 116 papers that have together received 2.1k indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (20 papers), Video Surveillance and Tracking Methods (15 papers), Medical Image Segmentation Techniques (14 papers), Cutaneous Melanoma Detection and Management (14 papers), Face and Expression Recognition (14 papers), Face recognition and analysis (14 papers), AI in cancer detection (13 papers) and Industrial Vision Systems and Defect Detection (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Ophthalmology (304 citations), Media Technology (253 citations), Radiology, Nuclear Medicine and Imaging (456 citations) and Oncology (432 citations). Jacob Scharcanski has collaborated with scholars based in Brazil, Canada and United States. Frequent co-authors include Pablo G. Cavalcanti, Daniel Welfer, Diane Ruschel Marinho, Cláudio Rosito Jung, Alexander Wong, Paul Fieguth, Diego H. Milone, C. T. J. Dodson, Maciel Zortea and A.N. Venetsanopoulos. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, Expert Systems with Applications, Computerized Medical Imaging and Graphics, Pattern Recognition and Pattern Recognition Letters.

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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