Geoffrey Everest Hinton
United Kingdom
Geoffrey Hinton, known as the “Godfather of Deep Learning,” is a pioneer in artificial intelligence. He developed key methods for training neural networks, including backpropagation. Hinton worked as an Engineering Fellow at Google and was a professor at the University of Toronto. His research transformed AI applications like image recognition and speech processing.
| Total Patents | 54 |
| Granted Patents | 29 |
| Associated Companies | |
| Field of Invention | Artificial Intelligence |
Geoffrey Everest Hinton’s portfolio has 54 patents belonging to 19 unique patent families. His patent belong to technological domains such as Vacuum Cleaner, Fan Assembly, Dryers and Humidifier.
Key Patents of Geoffrey Everest Hinton
Here are the top 5 patents filed by Geoffrey Everest Hinton that highlight his ground-breaking contributions to household technology:
| Publication Number | Title | Application Year | Technology Area (Lv 1) |
| US11003856B2 | Processing Text Using Neural Networks | 2019 | Image analysis |
| US9251437B2 | System And Method For Generating Training Cases For Image Classification | 2013 | Image analysis |
| US9704068B2 | System And Method For Labelling Aerial Images | 2013 | 2D Mapping |
| WO2024081778A1 | A Generalist Framework For Panoptic Segmentation Of Images And Videos | 2023 | Image and Video Segmentation |
| US10635972B1 | Recurrent Neural Networks With Rectified Linear Units | 2016 | AI/ML |
Join us in this venture to uncover the diverse technological areas Geoffrey Everest Hinton has patented inventions in. This article also discloses the patent filing trend, worldwide filing and research centers along with several other insights mined through the patent data set for the renowned inventor.
The data of inventors patents made available here is solely intended for informational purposes. Although we make every effort to maintain the accuracy and comprehensiveness of the provided information, we cannot guarantee that all data is completely free of errors or entirely up-to-date. If you happen to be the Inventor and wish to contribute additional data for your respective portfolio, kindly get in touch with us.
How Many Patents did Geoffrey Everest Hinton File Every Year?
Are you wondering why there is a drop in patent filing for the last two years? It is because a patent application can take up to 18 months to get published. Certainly, it doesn’t suggest a decrease in the patent filing.
| Year of Patents Filing or Grant | Geoffrey Everest Hinton Applications Filed | Geoffrey Everest Hinton Patents Granted |
| 2024 | 1 | 6 |
| 2023 | 6 | 4 |
| 2022 | 6 | 5 |
| 2021 | 4 | 2 |
| 2020 | 12 | 3 |
| 2019 | 3 | 4 |
| 2017 | 5 | 3 |
| 2016 | 2 | 2 |
| 2015 | 5 | – |
| 2013 | 9 | – |
How Many Geoffrey Everest Hinton patents are Alive/Dead?
Worldwide Patents
How Many Patents did Geoffrey Everest Hinton File in Different Countries?
Countries in which Geoffrey Everest Hinton Filed Patents
| Country | Patents |
| United States of America | 30 |
| Europe (EPO) | 7 |
| Australia | 2 |
| India | 1 |
| Austria | 1 |
| Brazil | 1 |
We also came across few intriguing inventions in the Geoffrey Everest Hinton patent portfolio. Read the summary of these ingenious innovations that showcase the incredible inventions of Geoffrey Everest Hinton’s technological ventures.
A system disclosed in patent, US11003856B2 creates unique numeric codes for text snippets by linking them to images. It sends a text snippet as a query to an image search engine, retrieves related images, and uses a neural network to convert each image into a numeric code. These codes are then combined into a single numeric representation of the text, bridging words and images for innovative AI applications.
A system for creating training images disclosed in patent US9251437B2 expands datasets for neural network training. It takes an existing image with a classification and uses an image processing module to apply color-space deformation to each pixel. The modified image retains the original classification, increasing the variety and size of the training set to improve neural network performance.
A system for creating images disclosed in patent US9704068B2 labeling aerial images uses a neural network to generate predicted map data. The network is trained with an objective function designed to handle noise in the map images, including both omission and registration noise, ensuring more accurate labeling
Well, this sums up the interesting summaries of the fascinating patents we discovered during our analysis. Keep reading to get more informative insights we mined through the Geoffrey Everest Hinton patent portfolio.
The chart below distributes patents filed by Geoffrey Everest Hinton in different countries on the basis of the technology protected in patents. It also represents the markets where Geoffrey Everest Hinton thinks it’s important to protect particular technology inventions.
R&D Focus: How Geoffrey Everest Hinton Research Focus Changes Over the Years?
10 Best Geoffrey Everest Hinton PatentsWO2019083553A1 is the most popular patent in the Geoffrey Everest Hinton’s portfolio. It has received 40 citations so far from companies like Seiko Epson Corporation, IBM and Beijing Baidu Netcom Technology.
Below is the list of 10 most cited patents of Geoffrey Everest Hinton:
| Publication Number | Citation Count |
| WO2019083553A1 | 40 |
| WO2014105866A1 | 32 |
| US9811775B2 | 28 |
| WO2014105865A1 | 26 |
| US9406017B2 | 25 |
| US10289962B2 | 8 |
| US20170228871A1 | 8 |
| US11003856B2 | 7 |
| US11354778B2 | 6 |
| US9251437B2 | 5 |