David Ha

1.4k citations
11 papers · 29 indexed · h-index 3
Topics
Face and Expression Recognition (3 papers)Machine Learning and Data Classification (3 papers)Neural Networks and Applications (2 papers)
Partner nations
JapanBelgiumSwitzerland

In The Last Decade

David Ha

10 papers receiving 27 citations

Peers

David Ha
Comparison fields: 5 of 22
  • Artificial Intelligence 20
  • Computer Vision and Pattern Recognition 10
  • Sociology and Political Science 5
  • Human-Computer Interaction 5
  • Developmental and Educational Psychology 5
Replace Torsten Illmann with:
Torsten Illmann Germany
Tingchen Fu China
Cyril Zhang United States
Chris Chinenye Emezue Germany
Marc Oliu Spain
Abhishek Dasgupta United Kingdom
Wenyi Hong China
Fereshte Khani United States
Jay Patravali United Kingdom
Deniz Oktay United States
David Ha relative to Torsten Illmann Germany Torsten Illmann's profile →
Citations per field
00.5×
Torsten Illmann · 1×
Citations per year

Countries citing papers authored by David Ha

Since Specialization
Citations

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

Fields of papers citing papers by David Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Ha

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 1
2 1
3 15
4 1
5 1
6
A Classification-Uncertainty-Based Criterion for Classification Boundary Selection
1
7 3
8 1
9
Generating Abstract Patterns with TensorFlow
1
10
k-medoids clustering algorithm
3
11
Handwriting Generation Demo in TensorFlow
1

About David Ha

David Ha is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Developmental and Educational Psychology, having authored 11 papers that have together received 29 indexed citations. Recurring topics across this work include Face and Expression Recognition (3 papers), Machine Learning and Data Classification (3 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Human-Computer Interaction (5 citations), Artificial Intelligence (20 citations) and Computer Vision and Pattern Recognition (10 citations). David Ha has collaborated with scholars based in Japan, Belgium and Switzerland. Frequent co-authors include Rasmus Palm, Sebastian Risi, Shigeru Katagiri, Miho Ohsaki, Jürgen Schmidhuber and Stéphane Maes. Their work appears in journals such as Journal of Signal Processing Systems, IEEE Transactions on Games and arXiv (Cornell University).

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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