Justus Piater
About
In The Last Decade
Justus Piater
156 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 120
- Computer Vision and Pattern Recognition 1.2k
- Control and Systems Engineering 1.0k
- Artificial Intelligence 971
- Biomedical Engineering 362
- Cognitive Neuroscience 314
Countries citing papers authored by Justus Piater
This map shows the geographic impact of Justus Piater'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 Justus Piater with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justus Piater more than expected).
Fields of papers citing papers by Justus Piater
This network shows the impact of papers produced by Justus Piater. 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 Justus Piater. The network helps show where Justus Piater may publish in the future.
Co-authorship network of co-authors of Justus Piater
This figure shows the co-authorship network connecting the top 25 collaborators of Justus Piater. A scholar is included among the top collaborators of Justus Piater 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 Justus Piater. Justus Piater is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 20 | |
| 3 | Learning missing edges via kernels in partially-known graphs. | 4 |
| 4 | IIS at ImageCLEF 2015: Multi-label Classification Task. | 3 |
| 5 | Using viseme recognition to improve a sign language translation system. | 9 |
| 6 | RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus | 74 |
| 7 | Grasp Densities for Grasp Refinement in Industrial Bin Picking | 0 |
| 8 | The SignSpeak Project - Bridging the Gap Between Signers and Speakers | 20 |
| 9 | 20 | |
| 10 | Vision as Inference in a Hierarchical Markov Network | 2 |
| 11 | Learning, then Compacting Visual Policies | 2 |
| 12 | Decision trees and random subwindows for object recognition | 13 |
| 13 | International Conference on Vision Systems | 6 |
| 14 | Incremental Rectification of Sports Fields in Video Streams With Application to Soccer | 3 |
| 15 | A Generic Approach For Image Classification Based On Decision Tree Ensembles And Local Sub-Windows | 25 |
| 16 | A Framework For Humanoid Control and Intelligence | 10 |
| 17 | Multi-Modal Tracking of Interacting Targets Using Gaussian Approximations | 15 |
| 18 | Constructive Feature Learning and the Development of Visual Expertise | 4 |
| 19 | A Framework for Learning Visual Discrimination | 2 |
| 20 | Interactive Training Of Pixel Classifiers Opens New Possibilities | 0 |
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.