PETUUM, INC.
14Patents
14Active
14Granted
50Portfolio score
Filing activity: Oct 27, 2017 → Sep 2, 2020
Most-cited patents
| Patent | Title | Area | Cited by | Status |
|---|---|---|---|---|
| US11087864B2 | Systems and methods for automatically tagging concepts to, and generating text reports for, medical images based on machine learning | Emerging Cross-Sectional Technologies | 4 | Active |
| US10832387B2 | Real-time intelligent image manipulation system | Physics | 2 | Active |
| US11301438B2 | System for automated data engineering for large scale machine learning | Physics | 1 | Active |
| US10699412B2 | Structure correcting adversarial network for chest X-rays organ segmentation | Physics | 1 | Active |
| US10782988B2 | Operating system for distributed enterprise artificial intelligence programs on data centers and the clouds | Electricity | 1 | Active |
| US11106998B2 | System with hybrid communication strategy for large-scale distributed deep learning | Electricity | 0 | Active |
| US10649806B2 | Elastic management of machine learning computing | Physics | 0 | Active |
| US11543830B2 | Unsupervised real-to-virtual domain unification for end-to-end highway driving | Physics | 0 | Active |
| US11282205B2 | Structure correcting adversarial network for chest x-rays organ segmentation | Physics | 0 | Active |
| US10706234B2 | Constituent centric architecture for reading comprehension | Physics | 0 | Active |
| US11101029B2 | Systems and methods for predicting medications to prescribe to a patient based on machine learning | Emerging Cross-Sectional Technologies | 0 | Active |
| US11348030B2 | System and methods for distributed machine learning with multiple data sources, multiple programming languages or frameworks, and multiple devices or infrastructures | Physics | 0 | Active |
| US11119992B2 | System for automated data engineering for large scale machine learning | Physics | 0 | Active |
| US11252260B2 | Efficient peer-to-peer architecture for distributed machine learning | Electricity | 0 | Active |
Source: USPTO / EPO open patent data. Counts and citation impact are objective bibliographic measures.