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Found 8 papers, 0 papers with code
FlowDepth: Decoupling Optical Flow for Self-Supervised Monocular Depth Estimation
To address these issues, existing approaches use additional semantic priori black-box networks to separate moving objects and improve the model only at the loss level.
MS-Net: A Multi-Path Sparse Model for Motion Prediction in Multi-Scenes
In the training stage, the motion prediction task under differentiated scenes is abstracted as a multi-task learning problem, an evolutionary algorithm is designed to encourage the network search of the optimal parameters for each scene while sharing common knowledge between different scenes.
Sparse and Faithful Explanations Without Sparse Models
In the loan denial example above, the SEV is 1 because only one factor is needed to explain why the loan was denied.
Interpretable End-to-End Driving Model for Implicit Scene Understanding
Driving scene understanding is to obtain comprehensive scene information through the sensor data and provide a basis for downstream tasks, which is indispensable for the safety of self-driving vehicles.
Perception Imitation: Towards Synthesis-free Simulator for Autonomous Vehicles
We propose a perception imitation method to simulate results of a certain perception model, and discuss a new heuristic route of autonomous driving simulator without data synthesis.
Multi-objective optimization and explanation for stroke risk assessment in Shanxi province
The experimental results showed that the QIDNN model with 7 interactive features achieve the state-of-art accuracy $83. 25\%$.
Analysis and classification of main risk factors causing stroke in Shanxi Province
Evaluation of the risk of getting stroke is important for the prevention and treatment of stroke in China.
Reducing transient energy growth in a channel flow using static output feedback control
In this study, we investigate static output feedback controllers for reducing transient energy growth of flow perturbations within linear and nonlinear simulations of a sub-critical channel flow.
Fluid Dynamics
