Vi Technology (United States)
In research, Vi Technology (United States) stands highest in Physical Sciences (#7,437 of 10,670 worldwide), 2022-now. Relative to its size it is most specialised in Computer Vision and Pattern Recognition and Computer Science (Computer Vision and Pattern Recognition is 13.7× its share of world research).
- World rank, 2022-now
- #14,975 of 22,385 · #21,561 all time
- Rank in United States
- #2,131 of 3,332
- Research works
- 347 ▲ 156% vs 2018-21
- Citations
- 8.5k 24.6 per fractional work
- Top-10% rate
- 21.4% all institutions 10.0%
- vs its own fields
- 0.95× 1.00× is exactly expected
- Open access
- 24% world 40%
- International
- 37% world 18%
What is Vi Technology (United States) known for in research?
The fields where it stands highest, 2022-now, ranked among every institution above the floor in each field.
| Field | World rank | Where that sits | Top-10% rate | Works | All time |
|---|---|---|---|---|---|
| Physical SciencesDomain | #7,437 of 10,670 | 28.4% | 78 | #9217 |
Each strip is that field's whole ranked pool, with the notch where Vi 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 average mark, because the average differs by field (from about 6% in Dentistry to 21% in Economics).
Which fields of science does Vi Technology (United States) work in?
In 2022-now, 74% of research at Vi Technology (United States) is in Physical Sciences, 11% in Social Sciences. Its largest fields are Computer Science (33%), Engineering (28%), Medicine (7%). It does 1.8× the world's share of Physical Sciences.
Each ring splits the one inside it: the four domains of science, their fields, their subfields. Size is fractional works in 2022-now. Every slice is a page; the interactive view zooms down to single topics and colours each by how much more of it this institution does than the world.
Its 4 domains and 24 fields, with their numbers
- Physical Sciences9473.7%
- Computer Science4233.0%
- Engineering3527.6%
- Materials Science65.0%
- Environmental Science43.0%
- Physics and Astronomy32.3%
- Earth and Planetary Sciences21.4%
- Chemistry10.8%
- Energy00.3%
- Mathematics00.2%
- Chemical Engineering00.1%
- Social Sciences1310.5%
- Health Sciences129.7%
- Medicine97.2%
- Health Professions32.4%
- Nursing00.1%
- Life Sciences86.1%
What does Vi Technology (United States) specialise in?
Where its research is concentrated relative to its size: Computer Vision and Pattern Recognition takes 13.7× the share of its output that it takes of world research.
- Computer Vision and Pattern RecognitionSubfield · 22.1 works14×
- Computer ScienceField · 42.3 works4.2×
Location quotient, a volume reading rather than an impact one. It surfaces small, lopsided specialities.
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, 4.2×. Every wedge is a field page.
All 24 fields, with their numbers
- Computer Science4.24×42 works
- Engineering1.84×35 works
- Materials Science1.43×6 works
- Neuroscience1.12×2 works
- Physics and Astronomy1.04×3 works
- Health Professions0.90×3 works
- Business, Management and Accounting0.88×4 works
- Earth and Planetary Sciences0.86×2 works
- Decision Sciences0.85×1 works
- Psychology0.72×3 works
- Economics, Econometrics and Finance0.62×2 works
- Environmental Science0.61×4 works
- Agricultural and Biological Sciences0.51×3 works
- Chemistry0.51×1 works
- Pharmacology, Toxicology and Pharmaceutics0.47×0 works
- Medicine0.37×9 works
- Energy0.31×0 works
- Biochemistry, Genetics and Molecular Biology0.30×2 works
- Arts and Humanities0.28×1 works
- Nursing0.21×0 works
- Social Sciences0.20×3 works
- Chemical Engineering0.19×0 works
- Mathematics0.18×0 works
- Immunology and Microbiology0.12×0 works
- Computer Science 4.2×
- Engineering 1.8×
- Materials Science 1.4×
- Neuroscience 1.1×
- Physics and Astronomy 1.0×
- Health Professions 0.9×
- Business, Management and Accounting 0.9×
- Earth and Planetary Sciences 0.9×
- Decision Sciences 0.8×
- Psychology 0.7×
- Economics, Econometrics and Finance 0.6×
- Environmental Science 0.6×
- Agricultural and Biological Sciences 0.5×
- Chemistry 0.5×
- Pharmacology, Toxicology and Pharmaceutics 0.5×
- Medicine 0.4×
- Energy 0.3×
- Biochemistry, Genetics and Molecular Biology 0.3×
- Arts and Humanities 0.3×
- Nursing 0.2×
- Social Sciences 0.2×
- Chemical Engineering 0.2×
- Mathematics 0.2×
- Immunology and Microbiology 0.1×
Who are the top researchers at Vi Technology (United States)?
Ranked on the quality score, Zeming Li, Jiajun Liang and Xuanyang Zhang lead among researchers whose main affiliation is Vi Technology (United States).
- 1
Zeming Li
United States · #164,098 worldwide 5.7k citations · 101 works
- 2
Jiajun Liang
United States · #1,789,476 worldwide 335 citations · 15 works
- 3
Xuanyang Zhang
United States · #2,154,311 worldwide 236 citations · 38 works
- 4
Gadi Krieger
United States · #3,686,446 worldwide 261 citations · 24 works
Which keywords describe research at Vi Technology (United States)?
By fractional works in 2022-now, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Unsupervised Learning, Convolutional Neural Networks, Image Processing, Machine Learning, Convolutional Networks and Depth Estimation.
- Text Classification
- Resolution Limits
- Local Descriptors
- Feature Matching
- Domain Adaptation
- Stereo Vision
- Microscopy
- Information Retrieval
- Nanofabrication
- Meta-Learning
- Mobile Robots
- Visual Question Answering
- Transfer Learning
- Representation Learning
- Object Detection
- Computer Vision
- Depth Estimation
- Image Processing
- Convolutional Neural Networks
- Neural Networks
- Deep Learning
- Machine Learning
- Unsupervised Learning
- Convolutional Networks
- Image Classification
- Image Recognition
- Healthcare
- Robotics
- Semantic Reasoning
- Semi-Supervised Learning
- Image Captioning
- Multimodal Fusion
- Object Recognition
- Localization
- Optical Flow
- 3D Mapping
- Electron Beam Lithography
- Few-Shot Learning
- Machine Vision
- SLAM
Size is fractional works in 2022-now 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 40 words are chosen for being large and distinctive. Each links to the topic it comes from most.
All 40 words, with their numbers
- Deep Learning29▲ 6.6×50 topics
- Neural Networks11▲ 5.7×18 topics
- Machine Learning10▲ 2.3×29 topics
- Convolutional Neural Networks6▲ 6.4×6 topics
- Unsupervised Learning6▲ 30×3 topics
- Image Processing5▲ 9.7×6 topics
- Convolutional Networks5▲ 30×3 topics
- Depth Estimation5▲ 46×2 topics
- Image Classification4▲ 19×2 topics
- Computer Vision4▲ 12×3 topics
- Image Recognition4▲ 22×1 topic
- Object Detection4▲ 23×1 topic
- Healthcare4▲ 2.8×10 topics
- Representation Learning4▲ 19×3 topics
- Robotics4▲ 11×5 topics
- Transfer Learning3▲ 13×3 topics
- Semantic Reasoning3▲ 28×2 topics
- Visual Question Answering3▲ 28×2 topics
- Semi-Supervised Learning3▲ 20×2 topics
- Mobile Robots3▲ 24×2 topics
- Image Captioning3▲ 39×1 topic
- Meta-Learning3▲ 26×2 topics
- Multimodal Fusion3▲ 39×1 topic
- Nanofabrication3▲ 36×2 topics
- Object Recognition3▲ 28×2 topics
- Information Retrieval3▲ 9.2×4 topics
- Localization3▲ 17×2 topics
- Microscopy3▲ 29×2 topics
- Optical Flow3▲ 42×1 topic
- Stereo Vision3▲ 42×1 topic
- 3D Mapping2▲ 28×1 topic
- Domain Adaptation2▲ 36×1 topic
- Electron Beam Lithography2▲ 213×1 topic
- Feature Matching2▲ 34×1 topic
- Few-Shot Learning2▲ 36×1 topic
- Local Descriptors2▲ 34×1 topic
- Machine Vision2▲ 9.2×3 topics
- Resolution Limits2▲ 213×1 topic
- SLAM2▲ 28×1 topic
- Text Classification2▲ 11×3 topics
Which research topics does Vi Technology (United States) publish most on?
By volume in 2022-now: Advanced Neural Network Applications, Multimodal Machine Learning Applications, Domain Adaptation and Few-Shot Learning and Advanced Vision and Imaging.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Advanced Neural Network Applications Computer Vision and Pattern Recognition 4 works
- 2 Multimodal Machine Learning Applications Computer Vision and Pattern Recognition 3 works
- 3 Domain Adaptation and Few-Shot Learning Artificial Intelligence 3 works
- 4 Advanced Vision and Imaging Computer Vision and Pattern Recognition 3 works
- 5 Robotics and Sensor-Based Localization Aerospace Engineering 2 works
- 6 Advancements in Photolithography Techniques Electrical and Electronic Engineering 2 works
- 7 Advanced Image and Video Retrieval Techniques Computer Vision and Pattern Recognition 2 works
- 8 Electron and X-Ray Spectroscopy Techniques Surfaces, Coatings and Films 2 works
- 9 Image Processing Techniques and Applications Media Technology 2 works
- 10 Smart Agriculture and AI Plant Science 2 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: 40% of research is openly available.
World: 18% is written across borders.
How has Vi Technology (United States)'s research output changed?
Output in 2022-2025 was 156% higher than in 2018-2021.
The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.
Its share of all research
Growing output can still be a shrinking share: all of science grows. This is Vi Technology (United States) as a percentage of every work published that year, 0.00031% in 2024.
Fractional works of Vi Technology (United States) over all fractional works that year. How the balance of science has shifted.
Other research institutions in Richardson
- The University of Texas at Dallas
- ZTE (United States)
- Society of Petroleum Engineers
- Language Computer (United States)
- Methodist Richardson Medical Center
- Memtronics (United States)
- IntelliEPI (United States)
- Photodigm (United States)
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners have tabs of their own, above.
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