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Found 5 papers, 0 papers with code
Vehicular Applications of Koopman Operator Theory -- A Survey
Koopman operator theory has proven to be a promising approach to nonlinear system identification and global linearization.
High-temporal-resolution event-based vehicle detection and tracking
Results show significant performance gains resembled by an improvement in the HOTA from 56. 6%, using only frames, to 64. 1% and 64. 9%, for the event and edge-based mask configurations combined with the two methods proposed, at the baseline framerate of 24Hz.
RMOPP: Robust Multi-Objective Post-Processing for Effective Object Detection
Over the last few decades, many architectures have been developed that harness the power of neural networks to detect objects in near real-time.
NeurAll: Towards a Unified Visual Perception Model for Automated Driving
In this paper, we propose a joint multi-task network design for learning several tasks simultaneously.
AuxNet: Auxiliary tasks enhanced Semantic Segmentation for Automated Driving
Decision making in automated driving is highly specific to the environment and thus semantic segmentation plays a key role in recognizing the objects in the environment around the car.
