Mohammad Saberian
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Signal Processing
- Computational Mechanics
- Biomedical Engineering
- Co-authors
- Nuno VasconcelosFarokh MarvastiMohammad Ali AkhaeeZhaowei CaiHamed Masnadi-ShiraziSoheil FeiziDavid KriegmanOscar Beijbom
- Topics
- Face and Expression Recognition (7 papers)Machine Learning and Data Classification (6 papers)Advanced Image and Video Retrieval Techniques (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of Machine Learning ResearchIEEE Transactions on Multimedia
- Partner nations
- United StatesIranUnited Kingdom
In The Last Decade
Mohammad Saberian
18 papers receiving 227 citations
Peers
Comparison fields: 5 of 46
- Computer Vision and Pattern Recognition 169
- Artificial Intelligence 113
- Signal Processing 21
- Computational Mechanics 14
- Biomedical Engineering 9
Countries citing papers authored by Mohammad Saberian
This map shows the geographic impact of Mohammad Saberian'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 Mohammad Saberian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Saberian more than expected).
Fields of papers citing papers by Mohammad Saberian
This network shows the impact of papers produced by Mohammad Saberian. 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 Mohammad Saberian. The network helps show where Mohammad Saberian may publish in the future.
Co-authorship network of co-authors of Mohammad Saberian
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Saberian. A scholar is included among the top collaborators of Mohammad Saberian 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 Mohammad Saberian. Mohammad Saberian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 28 | |
| 4 | Multiclass Boosting: Margins, Codewords, Losses, and Algorithms | 7 |
| 5 | 1 | |
| 6 | Large Margin Discriminant Dimensionality Reduction in Prediction Space | 3 |
| 7 | 12 | |
| 8 | Multiclass Boosting for Fast Multiclass Object Detection | 0 |
| 9 | Multi-Resolution Cascades for Multiclass Object Detection | 3 |
| 10 | Boosting algorithms for detector cascade learning | 10 |
| 11 | 1 | |
| 12 | 3 | |
| 13 | 18 | |
| 14 | 9 | |
| 15 | 23 | |
| 16 | Multiclass Boosting: Theory and Algorithms | 56 |
| 17 | Boosting Classifier Cascades | 19 |
| 18 | 31 | |
| 19 | 11 |
About Mohammad Saberian
Mohammad Saberian is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics, having authored 19 papers that have together received 240 indexed citations. Recurring topics across this work include Face and Expression Recognition (7 papers), Machine Learning and Data Classification (6 papers) and Advanced Image and Video Retrieval Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (169 citations), Artificial Intelligence (113 citations) and Signal Processing (21 citations). Mohammad Saberian has collaborated with scholars based in United States, Iran and United Kingdom. Frequent co-authors include Nuno Vasconcelos, Farokh Marvasti, Mohammad Ali Akhaee, Zhaowei Cai, Hamed Masnadi-Shirazi, Soheil Feizi, David Kriegman, Oscar Beijbom, José Costa Pereira and Maarten van Someren. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Machine Learning Research and IEEE Transactions on Multimedia.
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.