Hichem Snoussi
Hichem Snoussi publishes mostly in Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications, on topics such as Anomaly Detection Techniques and Applications, Video Surveillance and Tracking Methods and Energy Efficient Wireless Sensor Networks.
- World rank
- #862,795 of 7,710,434 ranked researchers
- Rank in France
- #41,421 of 324,115
- Works
- 411
- Citations
- 6.6k
- Citations per work
- 16.0
What does Hichem Snoussi research?
Hichem Snoussi's work is mostly in Computer Science (54%), Engineering (11%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences26764.9%
- Computer Science22254.1%
- Engineering4410.8%
- Everything else14435.1%
- 1Computer Vision and Pattern Recognition20% of their works
- 2Artificial Intelligence16% of their works
- 3Computer Networks and Communications14% of their works
- 4Electrical and Electronic Engineering7% of their works
- 5Signal Processing4% of their works
- 6Biomedical Engineering4% of their works
Research topics
- Anomaly Detection Techniques and Applications
- Video Surveillance and Tracking Methods
- Energy Efficient Wireless Sensor Networks
- Indoor and Outdoor Localization Technologies
- Target Tracking and Data Fusion in Sensor Networks
- Human Pose and Action Recognition
- Distributed Sensor Networks and Detection Algorithms
- Blind Source Separation Techniques
Which keywords describe Hichem Snoussi's research?
The keywords of their largest research topics: Deep Learning, Wireless Sensor Networks, Anomaly Detection, Unsupervised, Object Tracking, Visual Tracking, Energy-Efficient Protocols and Routing Techniques.
- Independent Component Analysis
- Distributed Detection
- Pose Estimation
- Particle Filters
- RF-Based Positioning
- Routing Techniques
- Visual Tracking
- Unsupervised
- Wireless Sensor Networks
- Deep Learning
- Anomaly Detection
- Object Tracking
- Energy-Efficient Protocols
- Indoor Localization
- Nonlinear Estimation
- Action Recognition
- Decentralized Estimation
- Blind Separation
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.
All 18 words, with their numbers
- Deep Learning1853 topics
- Wireless Sensor Networks1553 topics
- Anomaly Detection761 topic
- Unsupervised761 topic
- Object Tracking661 topic
- Visual Tracking661 topic
- Energy-Efficient Protocols641 topic
- Routing Techniques641 topic
- Indoor Localization511 topic
- RF-Based Positioning511 topic
- Nonlinear Estimation481 topic
- Particle Filters481 topic
- Action Recognition431 topic
- Pose Estimation431 topic
- Decentralized Estimation401 topic
- Distributed Detection401 topic
- Blind Separation251 topic
- Independent Component Analysis251 topic
Where does Hichem Snoussi work?
Hichem Snoussi's main affiliation in the publication record is Université de Technologie de Troyes, France.
How many publications and citations does Hichem Snoussi have?
OpenAlex counts 411 works and 6,582 citations for Hichem Snoussi, an h-index of 42, ranking #862,795 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
Discussion
Ask a question or share a note about Hichem Snoussi. Keep it to the research: no personal attacks, advertising or links. Any reader can report a post, which collapses it for everyone until it is opened.