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Found 5 papers, 2 papers with code
Neural Greedy Pursuit for Feature Selection
NGP is efficient in selecting $N$ features when $N \ll P$, and it provides a notion of feature importance in a descending order following the sequential selection procedure.
Multi-modal curb detection and filtering
We propose a robust curb detection and filtering technique based on the fusion of camera semantics and dense lidar point clouds.
Statistical model-based evaluation of neural networks
Using a statistical model-based data generation, we develop an experimental setup for the evaluation of neural networks (NNs).
Unified Multi-Modal Landmark Tracking for Tightly Coupled Lidar-Visual-Inertial Odometry
True integration of lidar features with standard visual features and IMU is made possible using a subtle passive synchronization of lidar and camera frames.
A ReLU Dense Layer to Improve the Performance of Neural Networks
We use a combination of random weights and rectified linear unit (ReLU) activation function to add a ReLU dense (ReDense) layer to the trained neural network such that it can achieve a lower training loss.
