Danish Vasan
- Signal Processing top 1%
- Computer Networks and Communications top 2%
- Artificial Intelligence top 5%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Mamoun AlazabZheng QinSobia WassanBabak SafaeiHamad NaeemMuhammad Rashid NaeemFarhan UllahShehzad Khalid
- Topics
- Advanced Malware Detection Techniques (9 papers)Anomaly Detection Techniques and Applications (5 papers)Network Security and Intrusion Detection (5 papers)
- Partner nations
- ChinaSaudi ArabiaPakistan
In The Last Decade
Danish Vasan
11 papers receiving 836 citations
Hit Papers
Peers
Comparison fields: 5 of 76
- Signal Processing 662
- Computer Networks and Communications 608
- Artificial Intelligence 407
- Information Systems 276
- Computer Vision and Pattern Recognition 97
Countries citing papers authored by Danish Vasan
This map shows the geographic impact of Danish Vasan'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 Danish Vasan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danish Vasan more than expected).
Fields of papers citing papers by Danish Vasan
This network shows the impact of papers produced by Danish Vasan. 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 Danish Vasan. The network helps show where Danish Vasan may publish in the future.
Co-authorship network of co-authors of Danish Vasan
This figure shows the co-authorship network connecting the top 25 collaborators of Danish Vasan. A scholar is included among the top collaborators of Danish Vasan 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 Danish Vasan. Danish Vasan 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 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 5 | |
| 7 | 25 | |
| 8 | 1 | |
| 9 | 76 | |
| 10 | Image-Based malware classification using ensemble of CNN architectures (IMCEC)breakdown → | 273 |
| 11 | 144 | |
| 12 | IMCFN: Image-based malware classification using fine-tuned convolutional neural network architecturebreakdown → | 341 |
| 13 | Visual Malware Classification Using Local and Global Malicious Pattern | 9 |
About Danish Vasan
Danish Vasan is a scholar working on Signal Processing, Software and Artificial Intelligence, having authored 13 papers that have together received 882 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (9 papers), Anomaly Detection Techniques and Applications (5 papers) and Network Security and Intrusion Detection (5 papers). The work is most often cited by research in Signal Processing (662 citations), Computer Networks and Communications (608 citations) and Software (73 citations). Danish Vasan has collaborated with scholars based in China, Saudi Arabia and Pakistan. Frequent co-authors include Mamoun Alazab, Zheng Qin, Sobia Wassan, Babak Safaei, Hamad Naeem, Muhammad Rashid Naeem, Farhan Ullah, Shehzad Khalid, Sohail Jabbar and Saqib Saeed. Their work appears in journals such as IEEE Transactions on Computers, Applied Soft Computing and Computer Networks.
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.