Hans Peter Graf

5.5k total citations
93 papers, 3.0k citations indexed

About

Hans Peter Graf is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Hans Peter Graf has authored 93 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Artificial Intelligence, 44 papers in Computer Vision and Pattern Recognition and 26 papers in Electrical and Electronic Engineering. Recurrent topics in Hans Peter Graf's work include Neural Networks and Applications (34 papers), Speech and Audio Processing (17 papers) and Advanced Memory and Neural Computing (15 papers). Hans Peter Graf is often cited by papers focused on Neural Networks and Applications (34 papers), Speech and Audio Processing (17 papers) and Advanced Memory and Neural Computing (15 papers). Hans Peter Graf collaborates with scholars based in United States, Germany and Japan. Hans Peter Graf's 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 and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Physics Letters and Journal of Applied Physics.

In The Last Decade

Hans Peter Graf

89 papers receiving 2.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hans Peter Graf United States 32 1.4k 1.4k 719 605 252 93 3.0k
豊 松尾 3 1.5k 1.0× 1.7k 1.3× 277 0.4× 296 0.5× 219 0.9× 5 3.6k
Adam Coates United States 17 2.5k 1.7× 2.0k 1.5× 335 0.5× 404 0.7× 450 1.8× 27 4.4k
James Martens Canada 13 1.3k 0.9× 2.0k 1.5× 308 0.4× 394 0.7× 171 0.7× 23 3.5k
Li Deng China 14 964 0.7× 2.0k 1.5× 606 0.8× 414 0.7× 70 0.3× 43 3.3k
Eduard Säckinger United States 19 1.3k 0.9× 1.3k 1.0× 1.6k 2.3× 318 0.5× 177 0.7× 31 4.3k
Y. Le Cun United States 20 1.4k 1.0× 1.4k 1.0× 266 0.4× 297 0.5× 225 0.9× 38 2.9k
Patrice Simard United States 25 1.4k 1.0× 1.5k 1.1× 198 0.3× 339 0.6× 117 0.5× 35 3.1k
Guillaume Desjardins Canada 11 2.0k 1.4× 3.3k 2.4× 359 0.5× 339 0.6× 231 0.9× 29 4.8k
M. Omair Ahmad Canada 35 2.6k 1.8× 630 0.5× 695 1.0× 1.5k 2.6× 242 1.0× 407 4.8k
Ahmed Bouridane United Kingdom 35 3.1k 2.2× 1.4k 1.0× 455 0.6× 1.2k 2.0× 88 0.3× 426 5.4k

Countries citing papers authored by Hans Peter Graf

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Saito, Akira, Koji Fujita, Masaharu Kobayashi, et al.. (2023). Development of multiple AI pipelines that predict neoadjuvant chemotherapy response of breast cancer using H&E‐stained tissues. The Journal of Pathology Clinical Research. 9(3). 182–194. 6 indexed citations
2.
Yamamoto, Yoichiro, Akira Saito, Ayako Tateishi, et al.. (2017). Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach. Scientific Reports. 7(1). 46732–46732. 32 indexed citations
3.
Oikawa, Kosuke, Akira Saito, Tomoharu Kiyuna, et al.. (2017). Pathological Diagnosis of Gastric Cancers with a Novel Computerized Analysis System. Journal of Pathology Informatics. 8(1). 5–5. 16 indexed citations
4.
Jakkula, Venkata, Srihari Cadambi, Srimat Chakradhar, et al.. (2009). A Massively Parallel Coprocessor for Convolutional Neural Networks. 53–60. 175 indexed citations
5.
Graf, Hans Peter, et al.. (2008). A Massively Parallel Digital Learning Processor. Neural Information Processing Systems. 21. 529–536. 26 indexed citations
6.
Jackel, L. D., Henry S. Baird, Bernhard E. Boser, et al.. (2002). A neural network approach to handprint character recognition. 1. 472–475. 2 indexed citations
7.
Chen, Tsuhan, et al.. (2002). A new frame interpolation scheme for talking head sequences. Proceedings - International Conference on Image Processing. 2. 591–594. 9 indexed citations
8.
Cosatto, Eric & Hans Peter Graf. (2000). Photo-realistic talking-heads from image samples. IEEE Transactions on Multimedia. 2(3). 152–163. 93 indexed citations
9.
Säckinger, Eduard & Hans Peter Graf. (1996). A board system for high-speed image analysis and neural networks. IEEE Transactions on Neural Networks. 7(1). 214–221. 7 indexed citations
10.
Simard, Patrice Y. & Hans Peter Graf. (1993). Backpropagation without Multiplication. Neural Information Processing Systems. 6. 232–239. 10 indexed citations
11.
Graf, Hans Peter & Eric Cosatto. (1993). Address Block Location with a Neural Net System. Neural Information Processing Systems. 6. 785–792. 2 indexed citations
12.
Graf, Hans Peter, et al.. (1991). Image Segmentation with Networks of Variable Scales. Neural Information Processing Systems. 4. 480–487. 3 indexed citations
13.
Graf, Hans Peter, et al.. (1990). Reconfigurable Neural Net Chip with 32K Connections. Neural Information Processing Systems. 3. 1032–1038. 5 indexed citations
14.
Satyanarayana, S., Y. Tsividis, & Hans Peter Graf. (1990). A reconfigurable analog VLSI neural and network. Neural Information Processing Systems. 758–768. 2 indexed citations
15.
Pataki, A., et al.. (1990). Spontaneous osteo-arthritis of the knee-joint in C57BL mice receiving chronic oral treatment with NSAID's or prednisone. Inflammation Research. 29(3-4). 210–217. 4 indexed citations
16.
Satyanarayana, S., Y. Tsividis, & Hans Peter Graf. (1989). A Reconfigurable Analog VLSI Neural Network Chip. Neural Information Processing Systems. 2. 758–768. 13 indexed citations
17.
Denker, John S., W.R. Gardner, Hans Peter Graf, et al.. (1988). Neural Network Recognizer for Hand-Written Zip Code Digits. Neural Information Processing Systems. 1. 323–331. 89 indexed citations
18.
Graf, Hans Peter, et al.. (1987). Microelectronic Implementations of Connectionist Neural Networks. Neural Information Processing Systems. 515–523. 4 indexed citations
19.
Graf, Hans Peter, L. D. Jackel, Richard Howard, et al.. (1986). VLSI implementation of a neural network memory with several hundreds of neurons. AIP conference proceedings. 151. 182–187. 32 indexed citations
20.
Graf, Hans Peter & H. Münzel. (1974). Excitation functions for α-particle reactions with molybdenum isotopes. Journal of Inorganic and Nuclear Chemistry. 36(12). 3647–3657. 63 indexed citations

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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