Navinfo Europe has a total of 46 patents globally, out of which 10 have been granted. Of these 46 patents, more than 97% patents are active. United States of America is where Navinfo Europe has filed the maximum number of patents, followed by Netherlands and Europe. Parallelly, United States of America seems to be the main focused R&D centre and also Netherlands is the origin country of Navinfo Europe.
Navinfo Europe was founded in the year 2014. The Company incorporates the European Advanced Research Lab and Corporate Development activities for NavInfo.
Do read about some of the most popular patents of Navinfo Europe which have been covered by us in this article and also you can find Navinfo Europe patents information, the worldwide patent filing activity and its patent filing trend over the years, and many other stats over Navinfo Europe patent portfolio.
How many patents does Navinfo Europe have?
Navinfo Europe has a total of 46 patents globally. These patents belong to 19 unique patent families. Out of 46 patents, 45 patents are active.
How Many Patents did Navinfo Europe 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 | Navinfo Europe Applications Filed | Navinfo Europe Patents Granted |
| 2023 | – | 4 |
| 2022 | 27 | 2 |
| 2021 | 9 | 4 |
| 2020 | 8 | – |
| 2019 | 2 | – |
How many Navinfo Europe patents are Alive/Dead?
How Many Patents did Navinfo Europe File in Different Countries?
Countries in which Navinfo Europe Filed Patents
| Country | Patents |
| United States Of America | 20 |
| Netherlands | 14 |
| Europe | 12 |
Where are Research Centres of Navinfo Europe Patents Located?
Best Navinfo Europe Patents
US20220156882A1 is the most popular patent in the Navinfo Europe portfolio. It has received 4 citations so far from company like Toyota Research Institute, Inc.
What Percentage of Navinfo Europe US Patent Applications were Granted?
Navinfo Europe (Excluding its subsidiaries) has filed 7 patent applications at USPTO so far (Excluding Design and PCT applications). Out of these 2 have been granted leading to a grant rate of 100.0%.
Below are the key stats of Navinfo Europe patent prosecution at the USPTO.
Which Law Firms Filed Most US Patents for Navinfo Europe?
| Law Firm | Total Applications | Success Rate |
| Peacock Law P C | 7 | 100.00% |
List of Navinfo Europe Patents
| Navinfo Europe Patents | Title |
| US11538166B2 | Semantic Segmentation Architecture |
| US11210547B2 | Real-Time Scene Understanding System |
| US20230289977A1 | Differencing Based Self-Supervised Scene Change Detection (D-Sscd) With Temporal Consistency |
| US20230281438A1 | Consistency-Regularization Based Approach For Mitigating Catastrophic Forgetting In Continual Learning |
| US20230281985A1 | Similarity Guided Progressive Decoder Fusion In Neural Networks Deep Learning |
| US20230281978A1 | Method To Add Inductive Bias Into Deep Neural Networks To Make Them More Shape-Aware |
| US20230281451A1 | Computer-Implemented Method Of Synaptic Consolidation And Experience Replay In A Dual Memory Architecture |
| US20230258471A1 | Ai Based Change Detection System For Executing A Method To Detect Changes In Geo-Tagged Videos To Update Hd Maps |
| US20230252279A1 | Self-Supervised Based Approach For Mitigating Catastrophic Forgetting In Continuous Learning |
| US20230252769A1 | Self-Supervised Mutual Learning For Boosting Generalization In Compact Neural Networks |
| US20230245463A1 | Computer-Implemented Method Of Self-Supervised Learning In Neural Network For Robust And Unified Estimation Of Monocular Camera Ego-Motion And Intrinsics |
| US20230237785A1 | Deep Learning Based Multi-Sensor Detection System For Executing A Method To Process Images From A Visual Sensor And From A Thermal Sensor For Detection Of Objects In Said Images |
| US20230123493A1 | Differencing Based Self-Supervised Pretraining For Change Detection (D-Sscd) |
| US20230114762A1 | Semantic Segmentation Architecture |
| US20230076893A1 | Complementary Learning System Based Experience Replay (Cls-Er) |
| US20220156882A1 | Computer-Implemented Method To Improve Scale Consistency And/Or Scale Awareness In A Model Of Self-Supervised Depth And Ego-Motion Prediction Neural Networks |
| US20220092320A1 | Method And System For Generating Ground-Truth Annotations Of Roadside Objects In Video Data |
| US20220044116A1 | Computer-Implemented Method Of Training A Computer-Implemented Deep Neural Network And Such A Network |
| US20210342589A1 | System And Method For Computing The 3D Position Of A Semantic Landmark In Images From The Real World |
| US20210166123A1 | Method For Training A Robust Deep Neural Network Model |
| EP4242983A1 | Differencing Based Self-Supervised Scene Change Detection (D-Sscd) With Temporal Consistency |
| EP4239525A1 | A Computer-Implemented Method Of Synaptic Consolidation And Experience Replay In A Dual Memory Architecture |
| EP4239532A1 | Similarity Guided Progressive Decoder Fusion In Neural Networks Deep Learning |
| EP4239523A1 | Method To Add Inductive Bias Into Deep Neural Networks To Make Them More Shape-Aware |
| EP4239524A1 | Consistency-Regularization Based Approach For Mitigating Catastrophic Forgetting In Continuous Learning |
| EP4231240A1 | Ai Based Change Detection System For Executing A Method To Detect Changes In Geo-Tagged Videos To Update Hd Maps |
| EP4224372A1 | Self-Supervised Based Approach For Mitigating Catastrophic Forgetting In Continuous Learning |
| EP4216107A1 | Computer-Implemented Method Of Self-Supervised Learning In Neural Network For Robust And Unified Estimation Of Monocular Camera Ego-Motion And Intrinsics |
| EP4167185A1 | Differentiating Based Self-Supervised Pretraining For Change Detection (D-Sscd) |
| EP4002215A1 | Method To Improve Scale Consistency And/Or Scale Awareness In A Model Of Self-Supervised Depth And Ego-Motion Prediction Neural Networks |
| EP3905198A1 | System And Method For Computing The 3D Position Of A Semantic Landmark In Images From The Real World |
| NL2031335C | Similarity Guided Progressive Decoder Fusion In Neural Networks Deep Learning |
| NL2031097B1 | Ai Based Change Detection System For Executing A Method To Detect Changes In Geo-Tagged Videos To Update Hd Maps |
| NL2031026C | Self-Supervised Based Approach For Mitigating Catastrophic Forgetting In Continual Learning |
| NL2030052B1 | Differentiating Based Self-Supervised Pretraining For Change Detection (D-Sscd) |
| NL2026491B1 | Method Of Training A Deep Neural Network And Such A Network |
| NL2025452B1 | System And Method For 3D Positioning A Landmark In Images From The Real World |
| NL2025236B1 | A Semantic Segmentation Architecture |
| NL2025214B1 | Method For Training A Robust Deep Neural Network Model |
| NL2031728A | Consistency-Regularization Based Approach For Mitigating Catastrophic Forgetting In Continuous Learning |
| NL2032131A | Differencing Based Self-Supervised Scene Change Detection (D-Sscd) With Temporal Consistency |
| NL2031938A | A Computer-Implemented Method Of Synaptic Consolidation And Experience Replay In A Dual Memory Architecture |
| NL2031495A | Method To Add Inductive Bias Into Deep Neural Networks To Make Them More Shape-Aware |
| NL2031098A | Computer-Implemented Method Of Self-Supervised Learning In Neural Network For Robust And Unified Estimation Of Monocular Camera Ego-Motion And Intrinsics |
| NL2026528A | – |
| EP3712811A1 | Real-Time Scene Understanding System |
What are Navinfo Europe key innovation segments?
What Technologies are Covered by Navinfo Europe?
The chart below distributes patents filed by Navinfo Europe