Inventor

SMOLYANSKIY NIKOLAI

US25 patents

⚠️ This page may combine multiple inventors who share the name “SMOLYANSKIY NIKOLAI”. Patents are grouped by organization below to help distinguish them — per-person disambiguation is on the roadmap.

SMOLYANSKIY NIKOLAI

NVIDIA CORP

Multi-view deep neural network for LiDAR perception

Stereo depth estimation using deep neural networks

Performing autonomous path navigation using deep neural networks

Deep neural network for segmentation of road scenes and animate object instances for autonomous driving applications

Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications

Stereo depth estimation using deep neural networks

Future trajectory predictions in multi-actor environments for autonomous machine

Multi-view deep neural network for LiDAR perception

Top-down object detection from LiDAR point clouds

Multi-view deep neural network for LiDAR perception

Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications

Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications

Stereo depth estimation using deep neural networks

Behavior planning for autonomous vehicles

Deep neural network for segmentation of road scenes and animate object instances for autonomous driving applications

Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications

Predicting image warping for structure from motion using neural networks

Segmentation of lidar range images

Performing autonomous path navigation using deep neural networks

Dynamic object detection using LiDAR data for autonomous machine systems and applications

MICROSOFT TECHNOLOGY LICENSING LLC

Vehicle trajectory determination to stabilize vehicle-captured video

Vehicle trajectory determination to stabilize vehicle-captured video

Immersive interactive telepresence

Collaborative camera viewpoint control for interactive telepresence

Selecting portions of vehicle-captured video to use for display