Dolby (United States)
In research, Dolby (United States) stands highest in Physical Sciences (#9,894 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 23.7× its share of world research).
- World rank, 2022-now
- #20,822 of 22,385 · #25,915 all time
- Rank in United States
- #3,083 of 3,332
- Research works
- 296 ▲ 102% vs 2018-21
- Citations
- 1.9k 6.3 per fractional work
- Top-10% rate
- 6.0% all institutions 10.0%
- vs its own fields
- 0.93× 1.00× is exactly expected
- Open access
- 18% world 40%
- International
- 21% world 18%
What is Dolby (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 | #9,894 of 10,670 | 4.2% | 61 | #13307 |
Each strip is that field's whole ranked pool, with the notch where Dolby (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 Dolby (United States) work in?
In 2022-now, 76% of research at Dolby (United States) is in Physical Sciences, 17% in Social Sciences. Its largest fields are Computer Science (52%), Engineering (19%), Business, Management and Accounting (7%). It does 1.9× 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 19 fields, with their numbers
- Physical Sciences7076.2%
- Computer Science4751.6%
- Engineering1819.3%
- Physics and Astronomy32.9%
- Environmental Science11.1%
- Chemistry10.7%
- Materials Science00.5%
- Mathematics00.1%
- Earth and Planetary Sciences00.1%
- Social Sciences1516.5%
- Life Sciences44.6%
- Health Sciences22.6%
- Medicine22.2%
- Health Professions00.5%
What does Dolby (United States) specialise in?
Where its research is concentrated relative to its size: Computer Vision and Pattern Recognition takes 23.7× the share of its output that it takes of world research.
- Computer Vision and Pattern RecognitionSubfield · 27.2 works24×
- Computer ScienceField · 47.0 works6.6×
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, 6.6×. Every wedge is a field page.
All 19 fields, with their numbers
- Computer Science6.63×47 works
- Neuroscience2.32×3 works
- Business, Management and Accounting2.12×6 works
- Physics and Astronomy1.31×3 works
- Engineering1.28×18 works
- Decision Sciences0.95×1 works
- Psychology0.84×2 works
- Arts and Humanities0.54×1 works
- Chemistry0.44×1 works
- Economics, Econometrics and Finance0.34×1 works
- Social Sciences0.31×4 works
- Environmental Science0.22×1 works
- Immunology and Microbiology0.18×0 works
- Health Professions0.17×0 works
- Materials Science0.15×0 works
- Biochemistry, Genetics and Molecular Biology0.12×1 works
- Medicine0.11×2 works
- Mathematics0.06×0 works
- Earth and Planetary Sciences0.04×0 works
- Computer Science 6.6×
- Neuroscience 2.3×
- Business, Management and Accounting 2.1×
- Physics and Astronomy 1.3×
- Engineering 1.3×
- Decision Sciences 0.9×
- Psychology 0.8×
- Arts and Humanities 0.5×
- Chemistry 0.4×
- Economics, Econometrics and Finance 0.3×
- Social Sciences 0.3×
- Environmental Science 0.2×
- Immunology and Microbiology 0.2×
- Health Professions 0.2×
- Materials Science 0.1×
- Biochemistry, Genetics and Molecular Biology 0.1×
- Medicine 0.1×
- Mathematics 0.1×
- Earth and Planetary Sciences 0.0×
Who are the top researchers at Dolby (United States)?
Ranked on the quality score, Grant A. Davidson, Scott J. Daly and Peng Yin lead among researchers whose main affiliation is Dolby (United States).
- 1
Grant A. Davidson
United States · #2,541,146 worldwide 750 citations · 40 works
- 2
Scott J. Daly
United States · #2,551,006 worldwide 4.5k citations · 158 works
- 3
Peng Yin
United States · #2,891,625 worldwide 1.1k citations · 67 works
- 4
Tsung–Wei Huang
United States · #2,975,010 worldwide 201 citations · 20 works
- 5
Timo Kunkel
United States · #3,061,771 worldwide 684 citations · 37 works
- 6
Dae Yeol Lee
United States · #3,142,302 worldwide 97 citations · 17 works
- 7
Mark Vinton
United States · #3,418,601 worldwide 158 citations · 17 works
- 8
Poppy A. C. Crum
United States · #3,493,258 worldwide 298 citations · 19 works
- 9
Tong Shao
United States · #3,643,387 worldwide 105 citations · 17 works
- 10
Taoran Lu
United States · #3,769,038 worldwide 401 citations · 36 works
Which keywords describe research at Dolby (United States)?
By fractional works in 2022-now, weighted toward what it does more of than the world: Deep Learning, Neural Networks, Convolutional Networks, Big Data, Convolutional Neural Networks, Depth Estimation, Unsupervised Learning and Video Coding.
- Visual Attention
- Deep Neural Networks
- Audio-Visual Speech Recognition
- Dehazing
- Visualization
- Machine Vision
- Sparse Representations
- Super-Resolution
- High Efficiency Video Coding (HEVC)
- Wavelet Compression
- JPEG2000
- Generative Adversarial Networks
- Stereo Vision
- Sparse Representation
- Analytics
- Video Coding
- Unsupervised Learning
- Convolutional Neural Networks
- Big Data
- Neural Networks
- Deep Learning
- Convolutional Networks
- Sustainability
- Depth Estimation
- Hyperspectral Imaging
- Supply Chain Management
- Business Intelligence
- Optical Flow
- Image Processing
- Wavelet Transform
- Medical Imaging
- H.264/AVC
- Image
- Image Denoising
- Computer Graphics
- Virtual Reality
- Contrast Enhancement
- Feature Extraction
- Cortical Connectivity
- Speech Enhancement
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▲ 9.3×37 topics
- Neural Networks14▲ 9.9×18 topics
- Convolutional Networks8▲ 66×3 topics
- Big Data7▲ 8.0×7 topics
- Sustainability7▲ 3.0×4 topics
- Convolutional Neural Networks6▲ 9.4×6 topics
- Depth Estimation6▲ 86×2 topics
- Unsupervised Learning6▲ 44×3 topics
- Hyperspectral Imaging6▲ 24×2 topics
- Video Coding6▲ 296×2 topics
- Supply Chain Management6▲ 6.8×2 topics
- Analytics5▲ 66×1 topic
- Business Intelligence5▲ 66×1 topic
- Sparse Representation5▲ 29×5 topics
- Optical Flow5▲ 106×1 topic
- Stereo Vision5▲ 106×1 topic
- Image Processing4▲ 11×3 topics
- Generative Adversarial Networks4▲ 51×2 topics
- Wavelet Transform3▲ 15×2 topics
- JPEG20003▲ 233×1 topic
- Medical Imaging3▲ 6.2×2 topics
- Wavelet Compression3▲ 233×1 topic
- H.264/AVC3▲ 419×1 topic
- High Efficiency Video Coding (HEVC)3▲ 419×1 topic
- Image3▲ 80×1 topic
- Super-Resolution3▲ 80×1 topic
- Image Denoising3▲ 71×1 topic
- Sparse Representations3▲ 71×1 topic
- Computer Graphics3▲ 110×1 topic
- Machine Vision3▲ 14×3 topics
- Virtual Reality3▲ 5.8×5 topics
- Visualization3▲ 51×1 topic
- Contrast Enhancement2▲ 63×1 topic
- Dehazing2▲ 63×1 topic
- Feature Extraction2▲ 5.4×2 topics
- Audio-Visual Speech Recognition2▲ 41×1 topic
- Cortical Connectivity2▲ 50×2 topics
- Deep Neural Networks2▲ 17×3 topics
- Speech Enhancement2▲ 41×1 topic
- Visual Attention2▲ 34×2 topics
Which research topics does Dolby (United States) publish most on?
By volume in 2022-now: Big Data and Business Intelligence, Advanced Vision and Imaging, Advanced Data Compression Techniques and Advanced Image Processing Techniques.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Big Data and Business Intelligence Management Information Systems 5 works
- 2 Advanced Vision and Imaging Computer Vision and Pattern Recognition 5 works
- 3 Advanced Data Compression Techniques Computer Vision and Pattern Recognition 3 works
- 4 Advanced Image Processing Techniques Computer Vision and Pattern Recognition 3 works
- 5 Video Coding and Compression Technologies Signal Processing 3 works
- 6 Image and Signal Denoising Methods Computer Vision and Pattern Recognition 3 works
- 7 Computer Graphics and Visualization Techniques Computer Graphics and Computer-Aided Design 3 works
- 8 Image Enhancement Techniques Computer Vision and Pattern Recognition 2 works
- 9 Speech and Audio Processing Signal Processing 2 works
- 10 Image Processing Techniques and Applications Media Technology 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 Dolby (United States)'s research output changed?
Output in 2022-2025 was 102% 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 Dolby (United States) as a percentage of every work published that year, 0.00051% in 2024.
Fractional works of Dolby (United States) over all fractional works that year. How the balance of science has shifted.
Other research institutions in San Francisco
- University of California, San Francisco
- San Francisco State University
- University of San Francisco
- Institute on Aging
- Golden Gate University
- Bechtel (United States)
- University of California Hastings College of the Law
- Cal Humanities
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners have tabs of their own, above.
Discussion
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