K J Joseph
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Aerospace Engineering
- Radiology, Nuclear Medicine and Imaging
- Media Technology top 10%
- Co-authors
- Fahad Shahbaz KhanSalman KhanVineeth N BalasubramanianAkshita GuptaMubarak ShahSanath NarayanJathushan RajasegaranRao Muhammad Anwer
- Topics
- Multimodal Machine Learning Applications (7 papers)Domain Adaptation and Few-Shot Learning (5 papers)Advanced Neural Network Applications (4 papers)
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)Research Archive of Indian Institute of Technology Hyderabad (Indian Institute of Technology Hyderabad)Proceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- IndiaUnited StatesAustralia
In The Last Decade
K J Joseph
12 papers receiving 525 citations
Hit Papers
Peers
Comparison fields: 5 of 72
- Computer Vision and Pattern Recognition 380
- Artificial Intelligence 301
- Aerospace Engineering 38
- Radiology, Nuclear Medicine and Imaging 33
- Media Technology 31
Countries citing papers authored by K J Joseph
This map shows the geographic impact of K J Joseph'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 K J Joseph with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K J Joseph more than expected).
Fields of papers citing papers by K J Joseph
This network shows the impact of papers produced by K J Joseph. 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 K J Joseph. The network helps show where K J Joseph may publish in the future.
Co-authorship network of co-authors of K J Joseph
This figure shows the co-authorship network connecting the top 25 collaborators of K J Joseph. A scholar is included among the top collaborators of K J Joseph 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 K J Joseph. K J Joseph is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 4 | |
| 4 | 2 | |
| 5 | 15 | |
| 6 | 4 | |
| 7 | 110 | |
| 8 | 23 | |
| 9 | Incremental Object Detection via Meta-Learning | 62 |
| 10 | Towards Open World Object Detectionbreakdown → | 294 |
| 11 | Meta-Consolidation for Continual Learning | 1 |
| 12 | 23 |
About K J Joseph
K J Joseph is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 12 papers that have together received 542 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (7 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (380 citations), Artificial Intelligence (301 citations) and Media Technology (31 citations). K J Joseph has collaborated with scholars based in India, United States and Australia. Frequent co-authors include Fahad Shahbaz Khan, Salman Khan, Vineeth N Balasubramanian, Akshita Gupta, Mubarak Shah, Sanath Narayan, Jathushan Rajasegaran, Rao Muhammad Anwer, B. Srinivasan and Srikrishna Karanam. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Research Archive of Indian Institute of Technology Hyderabad (Indian Institute of Technology Hyderabad) and Proceedings of the AAAI Conference on Artificial 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.