Pyke Tin

905 citations
84 papers · 582 · h-index 14

Impact in

Papers in

Pyke Tin

72 papers receiving 546 citations

Peers

Pyke Tin
Comparison fields: 5 of 92
  • Small Animals 122
  • Computer Vision and Pattern Recognition 235
  • Animal Science and Zoology 92
  • Food Science 99
  • Artificial Intelligence 109
Replace Yangyang Guo with:
Yangyang Guo China
Thi Thi Zin Japan
Alan Davy Ireland
Yuan Rao China
Mohit Taneja Ireland
Cristian Olariu Ireland
Jing Nie China
Yifei Chen China
Pyke Tin relative to Yangyang Guo China Yangyang Guo's profile →
Citations per field
00.5×10×14×
Yangyang Guo · 1×
Citations per year

Countries citing papers authored by Pyke Tin

Since Specialization
Citations

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

Fields of papers citing papers by Pyke Tin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Pyke Tin, 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 Pyke Tin Line = papers co-authored together Pyke Tin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201961
2 202338
3 202037
4 201134
5 202327
6 198520
7 201019
8 202418
9 198517
10 202017
11 202415
12 201614
13 201614
14 202114
15 202412
16 201312
17 202112
18
A Probability-based Model for Detecting Abandoned Objects in Video Surveillance Systems
201211
19 201910
20 20229

About Pyke Tin

Pyke Tin is a scholar working on Computer Vision and Pattern Recognition, Small Animals, Animal Science and Zoology, Food Science and Information Systems, having authored 84 papers that have together received 582 indexed citations. Recurring topics across this work include Animal Behavior and Welfare Studies (22 papers), Video Surveillance and Tracking Methods (20 papers), Effects of Environmental Stressors on Livestock (15 papers), Food Supply Chain Traceability (12 papers), Human Pose and Action Recognition (11 papers), Advanced Image and Video Retrieval Techniques (9 papers), Advanced Queuing Theory Analysis (7 papers) and Genetic and phenotypic traits in livestock (6 papers). The work is most often cited by research in Small Animals (122 citations), Computer Vision and Pattern Recognition (235 citations), Animal Science and Zoology (92 citations), Food Science (99 citations) and Artificial Intelligence (109 citations). Pyke Tin has collaborated with scholars based in Japan, Myanmar and United States. Frequent co-authors include Thi Thi Zin, Ikuo Kobayashi, Hiromitsu Hama, Yoichiro Horii, R. M. Phatarfod, J. Gani, Hiroki Tamura, Etsuo Chosa, Mitsuhiro Yokota and Jerry Chun‐Wei Lin. Their work appears in journals such as Journal of Applied Probability, Sensors, Scientific Reports, IEEE Transactions on Consumer Electronics and Advances in Applied Probability.

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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