Jing Peng
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 5%
- Computer Networks and Communications top 5%
- Sociology and Political Science top 10%
- Co-authors
- Ronald J. WilliamsBir BhanuDouglas R. HeisterkampHonghua DaiBikramjit BanerjeeDaniel ZengShaojie QiaoChen Liang
- Topics
- Image Retrieval and Classification Techniques (15 papers)Recommender Systems and Techniques (13 papers)Advanced Image and Video Retrieval Techniques (13 papers)
- Journals
- Angewandte Chemie International EditionPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Jing Peng
154 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 177
- Artificial Intelligence 1.0k
- Computer Vision and Pattern Recognition 573
- Information Systems 232
- Computer Networks and Communications 228
- Sociology and Political Science 221
Countries citing papers authored by Jing Peng
This map shows the geographic impact of Jing Peng'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 Jing Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing Peng more than expected).
Fields of papers citing papers by Jing Peng
This network shows the impact of papers produced by Jing Peng. 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 Jing Peng. The network helps show where Jing Peng may publish in the future.
Co-authorship network of co-authors of Jing Peng
This figure shows the co-authorship network connecting the top 25 collaborators of Jing Peng. A scholar is included among the top collaborators of Jing Peng 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 Jing Peng. Jing Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 27 | |
| 9 | 0 | |
| 10 | 28 | |
| 11 | 45 | |
| 12 | 10 | |
| 13 | 1 | |
| 14 | 16 | |
| 15 | A random walk model for item recommendation in folksonomies | 1 |
| 16 | 1 | |
| 17 | 5 | |
| 18 | Finite sample error bound for Parzen windows | 3 |
| 19 | Fast concurrent reinforcement learners | 21 |
| 20 | An Adaptive Metric Machine for Pattern Classification | 30 |
About Jing Peng
Jing Peng is a scholar working on Artificial Intelligence, Health Informatics and Computer Vision and Pattern Recognition, having authored 171 papers that have together received 2.5k indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (15 papers), Recommender Systems and Techniques (13 papers) and Advanced Image and Video Retrieval Techniques (13 papers). The work is most often cited by research in Artificial Intelligence (1.0k citations), Computer Vision and Pattern Recognition (573 citations) and Signal Processing (177 citations). Jing Peng has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Ronald J. Williams, Bir Bhanu, Douglas R. Heisterkamp, Honghua Dai, Bikramjit Banerjee, Daniel Zeng, Shaojie Qiao, Chen Liang, Kartik Hosanagar and Raghuram Iyengar. Their work appears in journals such as Angewandte Chemie International Edition, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.