Intelligent Fusion Technology (United States)
In research, Intelligent Fusion Technology (United States) stands highest in Physical Sciences (#10,107 of 21,541 worldwide), over all time.
- World rank, all time
- #17,407 of 42,892
- Rank in United States
- #3,775 of 8,685
- Research works
- 229 ▼ 35% vs 2013–17
- Citations
- 2.3k 10.2 per fractional work
- Top-10% rate
- 27.5% record average 16.5%
- Open access
- 20% world 28%
What is Intelligent Fusion Technology (United States) known for in research?
The fields where it stands highest, over all time, ranked among every institution above the floor in each field.
| Field | World rank | Where that sits | Top-10% rate | Works |
|---|---|---|---|---|
| Physical SciencesDomain | #10,107 of 21,541 | 29.3% | 206 |
Each strip is that field’s whole ranked pool, with the notch where Intelligent Fusion Technology (United States) sits in it, in the colour of the band that rank falls in. The track under the rate is the rate itself: it carries no world mark, because the world rate differs by field (from about 6% to 21% in this record).
Field profile
Location quotient across every field it publishes in: outside the ring is more than an institution of this size would be expected to publish, inside it is less.
Rings at 0.5×, 1× and 2×. Widest outward: Computer Science, 4.7×. Every wedge is a field page.
- Computer Science 4.7×
- Chemical Engineering 3.2×
- Engineering 2.9×
- Physics and Astronomy 1.8×
- Decision Sciences 1.8×
- Earth and Planetary Sciences 1.0×
- Economics, Econometrics and Finance 0.5×
- Psychology 0.4×
- Chemistry 0.4×
- Pharmacology, Toxicology and Pharmaceutics 0.3×
- Materials Science 0.3×
- Environmental Science 0.2×
- Medicine 0.2×
- Health Professions 0.1×
- Mathematics 0.1×
- Biochemistry, Genetics and Molecular Biology 0.1×
- Social Sciences 0.1×
Who are the top researchers at Intelligent Fusion Technology (United States)?
Ranked on the composite score, Genshe Chen lead among researchers whose main affiliation is Intelligent Fusion Technology (United States).
- 1 Genshe Chen United States · #268,081 worldwide 382 citations · 121 works
Which keywords describe research at Intelligent Fusion Technology (United States)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Wireless Communications, Neural Networks, Wireless Networks, Resource Allocation, Sensor Fusion, Internet of Things and Mobile Edge Computing.
- Robotics
- Energy Efficiency
- Trajectory Optimization
- Nonlinear Estimation
- Beamforming
- Remote Sensing
- Multiuser Detection
- Wireless Sensor Networks
- Sparse Representation
- Healthcare
- 5G Networks
- Power Control
- Security and Privacy
- Mobile Edge Computing
- Wireless Networks
- Machine Learning
- Neural Networks
- Deep Learning
- Wireless Communications
- Internet of Things
- Resource Allocation
- Security
- Sensor Fusion
- Channel Estimation
- Convolutional Neural Networks
- Channel Assignment
- State Estimation
- CDMA Systems
- Orbit Determination
- Signal Processing
- Multi-Agent Systems
- Particle Filters
- UAV Networks
- MIMO Radar
- Waveform Design
Size is fractional works in 2022–2025 in the topics tagged with each word; colour is the word's share of this institution's work against its share of the world's. The 35 words are chosen for being large and distinctive. Each links to the topic it comes from most.
All 35 words, with their numbers
- Deep Learning7▲ 5.3×25 topics
- Neural Networks3▲ 4.5×11 topics
- Wireless Communications3▲ 38×5 topics
- Machine Learning2▲ 1.89×12 topics
- Internet of Things2▲ 6.0×7 topics
- Wireless Networks2▲ 33×5 topics
- Resource Allocation2▲ 27×4 topics
- Mobile Edge Computing2▲ 29×2 topics
- Security2▲ 7.1×6 topics
- Security and Privacy2▲ 24×2 topics
- Sensor Fusion2▲ 43×3 topics
- Power Control2▲ 117×2 topics
- Channel Estimation2▲ 45×4 topics
- 5G Networks1▲ 18×4 topics
- Convolutional Neural Networks1▲ 4.7×6 topics
- Healthcare1▲ 3.1×5 topics
- Channel Assignment1▲ 99×2 topics
- Sparse Representation1▲ 17×4 topics
- State Estimation1▲ 69×2 topics
- Wireless Sensor Networks1▲ 7.2×5 topics
- CDMA Systems1▲ 237×1 topic
- Multiuser Detection1▲ 237×1 topic
- Orbit Determination1▲ 70×2 topics
- Remote Sensing1▲ 2.5×4 topics
- Signal Processing1▲ 22×3 topics
- Beamforming1▲ 25×3 topics
- Multi-Agent Systems1▲ 15×3 topics
- Nonlinear Estimation1▲ 114×1 topic
- Particle Filters1▲ 114×1 topic
- Trajectory Optimization1▲ 50×1 topic
- UAV Networks1▲ 67×1 topic
- Energy Efficiency1▲ 2.7×6 topics
- MIMO Radar1▲ 76×2 topics
- Robotics1▲ 11×2 topics
- Waveform Design1▲ 71×2 topics
Which research topics does Intelligent Fusion Technology (United States) publish most on?
By volume in 2022–2025: Wireless Communication Networks Research, UAV Applications and Optimization, Target Tracking and Data Fusion in Sensor Networks and GNSS positioning and interference.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Wireless Communication Networks Research Computer Networks and Communications 1 works
- 2 UAV Applications and Optimization Aerospace Engineering 1 works
- 3 Target Tracking and Data Fusion in Sensor Networks Artificial Intelligence 1 works
- 4 GNSS positioning and interference Aerospace Engineering 1 works
- 5 Robotics and Sensor-Based Localization Aerospace Engineering 1 works
- 6 IoT and Edge/Fog Computing Computer Networks and Communications 1 works
- 7 Radar Systems and Signal Processing Aerospace Engineering 1 works
- 8 Digital Media Forensic Detection Computer Vision and Pattern Recognition 1 works
- 9 Infrared Target Detection Methodologies Aerospace Engineering 1 works
- 10 Inertial Sensor and Navigation Aerospace Engineering 1 works
How open and international is its research?
Against the world’s own shares — the tick on each track. Both are shares of its output, so they sit on one scale and can be read against each other as well as against the world.
World: 28% of research is openly available.
World: 19% is written across borders.
How has Intelligent Fusion Technology (United States)'s research output changed?
Output in 2018–2022 was 35% lower than in 2013–2017.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
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Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners are in the interactive view on the map.