Issam Laradji
- Information Systems top 2%
- Artificial Intelligence top 5%
- Software top 2%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Lahouari GhoutiMohammad AlshayebPau RodríguezDavid VázquezSimon Lacoste-JulienMark SchmidtM. CacciaPedro O. Pinheiro
- Topics
- Advanced Neural Network Applications (4 papers)Advanced Image and Video Retrieval Techniques (4 papers)Multimodal Machine Learning Applications (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceScientific ReportsInformation and Software Technology
- Partner nations
- CanadaUnited StatesSaudi Arabia
In The Last Decade
Issam Laradji
20 papers receiving 573 citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Information Systems 259
- Artificial Intelligence 236
- Software 231
- Computer Vision and Pattern Recognition 163
- Computer Networks and Communications 98
Countries citing papers authored by Issam Laradji
This map shows the geographic impact of Issam Laradji'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 Issam Laradji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Issam Laradji more than expected).
Fields of papers citing papers by Issam Laradji
This network shows the impact of papers produced by Issam Laradji. 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 Issam Laradji. The network helps show where Issam Laradji may publish in the future.
Co-authorship network of co-authors of Issam Laradji
This figure shows the co-authorship network connecting the top 25 collaborators of Issam Laradji. A scholar is included among the top collaborators of Issam Laradji 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 Issam Laradji. Issam Laradji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 23 | |
| 9 | 32 | |
| 10 | 3 | |
| 11 | 61 | |
| 12 | 27 | |
| 13 | 24 | |
| 14 | 19 | |
| 15 | Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning | 23 |
| 16 | 31 | |
| 17 | 3 | |
| 18 | 3 | |
| 19 | Software defect prediction using ensemble learning on selected featuresbreakdown → | 288 |
| 20 | 0 |
About Issam Laradji
Issam Laradji is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 24 papers that have together received 594 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Software (231 citations), Information Systems (259 citations) and Computer Vision and Pattern Recognition (163 citations). Issam Laradji has collaborated with scholars based in Canada, United States and Saudi Arabia. Frequent co-authors include Lahouari Ghouti, Mohammad Alshayeb, Pau Rodríguez, David Vázquez, Simon Lacoste-Julien, Mark Schmidt, M. Caccia, Pedro O. Pinheiro, David Vázquez and Dzmitry Bahdanau. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Information and Software Technology.
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.