Lin Xu
34Patents
6h-index
42Co-inventors
65Inventor score
Filing activity: Jun 12, 2006 → Sep 22, 2023
Most-cited inventions
| Patent | Title | Area | Cited by | Status |
|---|---|---|---|---|
| US9299582B2 | Selective etch for metal-containing materials | Electricity | 153 | Active |
| US9349605B1 | Oxide etch selectivity systems and methods | Electricity | 152 | Active |
| US9287134B2 | Titanium oxide etch | Electricity | 152 | Active |
| US9472417B2 | Plasma-free metal etch | Electricity | 136 | Active |
| US9711366B2 | Selective etch for metal-containing materials | Electricity | 115 | Active |
| US9768034B1 | Removal methods for high aspect ratio structures | Electricity | 115 | Active |
| US8172742B2 | Magnetic stimulation apparatus for central nervous system, circuit and use thereof, and method of using the apparatus | Human Necessities | 3 | Active |
| US11341368B2 | Methods and systems for advanced and augmented training of deep neural networks using synthetic data and innovative generative networks | Physics | 3 | Active |
| US10204795B2 | Flow distribution plate for surface fluorine reduction | Electricity | 2 | Active |
| US11263490B2 | Methods and systems for budgeted and simplified training of deep neural networks | Physics | 2 | Active |
| US10685262B2 | Object recognition based on boosting binary convolutional neural network features | Physics | 2 | Active |
| US10424464B2 | Oxide etch selectivity systems and methods | Electricity | 2 | Active |
| US10615047B2 | Systems and methods to form airgaps | Electricity | 1 | Active |
| US11107189B2 | Methods and systems using improved convolutional neural networks for image processing | Physics | 1 | Active |
| US10468267B2 | Water-free etching methods | Electricity | 1 | Active |
| US10424463B2 | Oxide etch selectivity systems and methods | Electricity | 1 | Active |
| US10430694B2 | Fast and accurate skin detection using online discriminative modeling | Physics | 1 | Active |
| US10846560B2 | GPU optimized and online single gaussian based skin likelihood estimation | Physics | 1 | Active |
| US11803739B2 | Methods and systems for budgeted and simplified training of deep neural networks | Physics | 1 | Active |
| US10854450B2 | Methods for repairing substrate lattice and selective epitaxy processing | Electricity | 0 | Active |
| US11335565B2 | Systems and methods to form airgaps | Electricity | 0 | Active |
| US11790223B2 | Methods and systems for boosting deep neural networks for deep learning | Physics | 0 | Active |
| US11551335B2 | Methods and systems using camera devices for deep channel and convolutional neural network images and formats | Electricity | 0 | Active |
| US11887001B2 | Method and apparatus for reducing the parameter density of a deep neural network (DNN) | Physics | 0 | Active |
| US12217163B2 | Methods and systems for budgeted and simplified training of deep neural networks | Physics | 0 | Active |
Source: USPTO / EPO open patent data. Inventor disambiguation is heuristic; counts are objective bibliographic measures.