Hans Peter Graf
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 1%
- Electrical and Electronic Engineering top 5%
- Signal Processing top 1%
- Control and Systems Engineering top 5%
- Co-authors
- Eric CosattoL. D. JackelGerasimos PotamianosD. HendersonRichard HowardSrimat ChakradharSrihari CadambiLéon Bottou
- Topics
- Neural Networks and Applications (34 papers)Speech and Audio Processing (17 papers)Advanced Memory and Neural Computing (15 papers)
- Journals
- SHILAP Revista de lepidopterologíaApplied Physics LettersJournal of Applied Physics
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Hans Peter Graf
89 papers receiving 2.8k citations
Peers
Comparison fields: 5 of 149
- Computer Vision and Pattern Recognition 1.4k
- Artificial Intelligence 1.4k
- Electrical and Electronic Engineering 719
- Signal Processing 605
- Control and Systems Engineering 252
Countries citing papers authored by Hans Peter Graf
This map shows the geographic impact of Hans Peter Graf'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 Hans Peter Graf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hans Peter Graf more than expected).
Fields of papers citing papers by Hans Peter Graf
This network shows the impact of papers produced by Hans Peter Graf. 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 Hans Peter Graf. The network helps show where Hans Peter Graf may publish in the future.
Co-authorship network of co-authors of Hans Peter Graf
This figure shows the co-authorship network connecting the top 25 collaborators of Hans Peter Graf. A scholar is included among the top collaborators of Hans Peter Graf 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 Hans Peter Graf. Hans Peter Graf is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 32 | |
| 3 | 16 | |
| 4 | 175 | |
| 5 | A Massively Parallel Digital Learning Processor | 26 |
| 6 | 2 | |
| 7 | 9 | |
| 8 | 93 | |
| 9 | 7 | |
| 10 | Backpropagation without Multiplication | 10 |
| 11 | Address Block Location with a Neural Net System | 2 |
| 12 | Image Segmentation with Networks of Variable Scales | 3 |
| 13 | Reconfigurable Neural Net Chip with 32K Connections | 5 |
| 14 | A reconfigurable analog VLSI neural and network | 2 |
| 15 | 4 | |
| 16 | A Reconfigurable Analog VLSI Neural Network Chip | 13 |
| 17 | Neural Network Recognizer for Hand-Written Zip Code Digits | 89 |
| 18 | Microelectronic Implementations of Connectionist Neural Networks | 4 |
| 19 | 32 | |
| 20 | 63 |
About Hans Peter Graf
Hans Peter Graf is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 93 papers that have together received 3.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (34 papers), Speech and Audio Processing (17 papers) and Advanced Memory and Neural Computing (15 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.4k citations), Signal Processing (605 citations) and Artificial Intelligence (1.4k citations). Hans Peter Graf has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Eric Cosatto, L. D. Jackel, Gerasimos Potamianos, D. Henderson, Richard Howard, Srimat Chakradhar, Srihari Cadambi, Léon Bottou, Vladimir Vapnik and J. S. Denker. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Physics Letters and Journal of Applied Physics.
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.