Road scene understanding by occupancy grid learning from sparse radar clusters using semantic segmentation

Keyphrases

• Autonomous Driving 33%
• Autonomous Vehicles 33%
• Computer Vision Techniques 33%
• Data Noise 33%
• Data Sparsity 33%
• Data-driven Approach 33%
• Deep Learning Technology 33%
• Drivable Area 33%
• Filter Approach 33%
• Inverse Sensor Model 33%
• Large Margin 33%
• LiDAR 33%
• Long Range Sensing 33%
• Naturalistic Driving Study 33%
• Noise Characteristics 33%
• NuScenes 33%
• Occupancy 33%
• Occupancy Grid 100%
• Occupancy Grid Mapping 100%
• Radar Data 66%
• Radar Sensor 33%
• Recent Advances 33%
• Road Obstacle 33%
• Road Scene Understanding 100%
• Safe Autonomous Driving 33%
• Segmentation Problem 33%
• Semantic Segmentation 100%
• Severe Weather Conditions 33%

Computer Science

• Autonomous Driving 100%
• Autonomous Vehicles 50%
• Computer Vision 50%
• Deep Learning 50%
• Driven Approach 50%
• Image Segmentation 100%
• Learning Technology 50%
• Scene Understanding 100%
• Segmentation Task 50%
• Sparsity 50%
• Weather Condition 50%

Engineering

• Computervision 33%
• Deep Learning 33%
• Filtration 33%
• Ground Truth 33%
• Optical Radar 33%
• Radar Data 66%
• Radar Sensor 33%
• Road 100%
• Sensor Model 33%
• Sparsity 33%
• Tasks 66%