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Researcher · Goethe Institut · Germany

Peter Waszkewitz

Peter Waszkewitz publishes mostly in Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition and Computational Mechanics, on topics such as Industrial Vision Systems and Defect Detection, Physics and Engineering Research Articles and Image and Object Detection Techniques.

OpenAlex
World rank
#3,562,489
of 7,710,434 ranked researchers
Rank in Germany
#178,161
of 364,343
Works
29
Citations
112
Citations per work
3.9
h-index
4
i10-index 4Top 87% in Industrial and Manufacturing Engineering (Engineering)
Peter Waszkewitz

What does Peter Waszkewitz research?

Peter Waszkewitz's work is mostly in Engineering (40%), Computer Science (21%), Environmental Science (5%).

Physical Sciences: 19 works · 65.5% of their workEngineering: 11 works · 39.6% of their workIndustrial and Manufacturing Engineering: 7 works · 24.1% of their workComputational Mechanics: 4 works · 15.5% of their workComputer Science: 6 works · 20.7% of their workComputer Vision and Pattern Recognition: 6 works · 20.7% of their workEnvironmental Science: 2 works · 5.2% of their workEnvironmental Engineering: 2 works · 5.2% of their workEverything else: 8 works · 25.9% of their workSocial Sciences: 2 works · 8.6% of their workBusiness, Management and Accounting: 2 works · 5.2% of their workManagement of Technology and Innovation: 2 works · 5.2% of their workArts and Humanities: 1 works · 3.4% of their workHistory and Philosophy of Science: 1 works · 3.4% of their workTHEIR WORKPeter Waszkewitz29works
Physical Sciences66%Social Sciences9%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Engineering1139.6%
    2. Computer Science620.7%
    3. Environmental Science25.2%
  2. Everything else825.9%
    1. Business, Management and Accounting25.2%
    2. Arts and Humanities13.4%
  1. 1Industrial and Manufacturing Engineering24% of their works
  2. 2Computer Vision and Pattern Recognition21% of their works
  3. 3Computational Mechanics16% of their works
  4. 4Environmental Engineering5% of their works
  5. 5Management of Technology and Innovation5% of their works
  6. 6History and Philosophy of Science3% of their works

Research topics

Which keywords describe Peter Waszkewitz's research?

The keywords of their largest research topics: Deep Learning, Texture Analysis, Fabric Defect Detection, Machine Vision, Fluid Dynamics, Renewable Energy, Hough Transform and Line Detection.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most.

All 18 words, with their numbers
  1. Deep Learning112 topics
  2. Texture Analysis112 topics
  3. Fabric Defect Detection91 topic
  4. Machine Vision91 topic
  5. Fluid Dynamics71 topic
  6. Renewable Energy71 topic
  7. Hough Transform41 topic
  8. Line Detection41 topic
  9. Business Models31 topic
  10. Digital Transformation31 topic
  11. Flexible Automation31 topic
  12. Forest Carbon Stocks31 topic
  13. Lidar Remote Sensing31 topic
  14. Reconfigurable Manufacturing Systems31 topic
  15. Fragmented Objects21 topic
  16. Image Segmentation21 topic
  17. Medical Image Analysis21 topic
  18. Reconstruction21 topic

Where does Peter Waszkewitz work?

Peter Waszkewitz's main affiliation in the publication record is Goethe Institut, Germany.

How many publications and citations does Peter Waszkewitz have?

OpenAlex counts 29 works and 112 citations for Peter Waszkewitz, an h-index of 4, ranking #3,562,489 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

Discussion

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