Silicon Technologies (United States)
- World rank, all time
- #38,065 of 42,892
- Rank in United States
- #8,005 of 8,685
- Research works
- 125 ▲ 306% vs 2013–17
- Citations
- 1.2k 9.4 per fractional work
- Top-10% rate
- 18.7% record average 16.5%
- Open access
- 26% world 28%
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.
- Computer Science 4.2×
- Engineering 3.2×
- Physics and Astronomy 1.5×
- Biochemistry, Genetics and Molecular Biology 1.1×
- Psychology 0.8×
- Pharmacology, Toxicology and Pharmaceutics 0.5×
- Materials Science 0.5×
- Energy 0.3×
- Arts and Humanities 0.3×
- Mathematics 0.3×
- Chemistry 0.2×
- Neuroscience 0.1×
- Earth and Planetary Sciences 0.1×
- Environmental Science 0.1×
- Economics, Econometrics and Finance 0.1×
- Agricultural and Biological Sciences 0.1×
- Medicine 0.1×
- Social Sciences 0.0×
Which keywords describe research at Silicon Technologies (United States)?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Deep Learning, Machine Learning, Image Processing, Convolutional Neural Networks, CMOS Technology, Power Optimization, Neural Networks and Embedded Cores.
- Bioimage Analysis
- Generative Adversarial Networks
- Test Data Compression
- Convolutional Networks
- CMOS Technology
- Convolutional Neural Networks
- Machine Learning
- Deep Learning
- Neural Networks
- Image Processing
- Power Optimization
- Embedded Cores
- Delta-Sigma Modulator
- Integrated Circuits
- High-Content Screening
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 15 words are chosen for being large and distinctive. Each links to the topic it comes from most.
All 15 words, with their numbers
- Deep Learning6▲ 6.3×19 topics
- Machine Learning3▲ 2.8×8 topics
- Neural Networks2▲ 4.0×5 topics
- Convolutional Neural Networks1▲ 7.0×6 topics
- Image Processing1▲ 11×2 topics
- CMOS Technology1▲ 58×4 topics
- Power Optimization1▲ 175×2 topics
- Convolutional Networks1▲ 30×2 topics
- Embedded Cores1▲ 287×1 topic
- Test Data Compression1▲ 287×1 topic
- Delta-Sigma Modulator1▲ 122×2 topics
- Generative Adversarial Networks1▲ 47×2 topics
- Integrated Circuits1▲ 26×3 topics
- Bioimage Analysis1▲ 100×1 topic
- High-Content Screening1▲ 100×1 topic
Which research topics does Silicon Technologies (United States) publish most on?
By volume in 2022–2025: VLSI and Analog Circuit Testing, Cell Image Analysis Techniques, VLSI and FPGA Design Techniques and Advancements in PLL and VCO Technologies.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 VLSI and Analog Circuit Testing Hardware and Architecture 1 works
- 2 Cell Image Analysis Techniques Biophysics 1 works
- 3 VLSI and FPGA Design Techniques Electrical and Electronic Engineering 1 works
- 4 Advancements in PLL and VCO Technologies Electrical and Electronic Engineering 1 works
- 5 Advanced Image Processing Techniques Computer Vision and Pattern Recognition 1 works
- 6 Integrated Circuits and Semiconductor Failure Analysis Electrical and Electronic Engineering 1 works
- 7 Fault Detection and Control Systems Control and Systems Engineering 0 works
- 8 Advanced Multi-Objective Optimization Algorithms Computational Theory and Mathematics 0 works
- 9 Advanced Vision and Imaging Computer Vision and Pattern Recognition 0 works
- 10 Image and Signal Denoising Methods Computer Vision and Pattern Recognition 0 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 Silicon Technologies (United States)'s research output changed?
Output in 2018–2022 was 306% higher 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.
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.