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Self-Driving Cars

Self-driving cars : the task of making a car that can drive itself without human guidance.

( Image credit: Learning a Driving Simulator )

Papers

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Showing 401–425 of 514 papers

TitleStatusHype
StarNet: Targeted Computation for Object Detection in Point Clouds—0
How far should self-driving cars see? Effect of observation range on vehicle self-localization—0
Neural Image Compression and ExplanationCode0
Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization—0
To Learn or Not to Learn: Visual Localization from Essential Matrices—0
EnSyth: A Pruning Approach to Synthesis of Deep Learning Ensembles—0
End-to-end sensor modeling for LiDAR Point Cloud—0
Metamorphic Detection of Adversarial Examples in Deep Learning Models With Affine Transformations—0
Large-scale 3D point cloud representations via graph inception networks with applications to autonomous driving—0
A Hierarchical Architecture for Sequential Decision-Making in Autonomous Driving using Deep Reinforcement LearningCode0
Deep Learning in the Automotive Industry: Recent Advances and Application Examples—0
LioNets: Local Interpretation of Neural Networks through Penultimate Layer DecodingCode0
Lidar based Detection and Classification of Pedestrians and Vehicles Using Machine Learning Methods—0
On Single Source Robustness in Deep Fusion ModelsCode0
Novelty Detection via Network Saliency in Visual-based Deep Learning—0
Key Ingredients of Self-Driving Cars—0
Y-GAN: A Generative Adversarial Network for Depthmap Estimation from Multi-camera Stereo Images—0
What Does It Mean to Learn in Deep Networks? And, How Does One Detect Adversarial Attacks?—0
Asymptotically Unambitious Artificial General Intelligence—0
Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural NetworksCode0
Understanding Pedestrian-Vehicle Interactions with Vehicle Mounted Vision: An LSTM Model and Empirical Analysis—0
Mitigating Deep Learning Vulnerabilities from Adversarial Examples Attack in the Cybersecurity Domain—0
Training a Fast Object Detector for LiDAR Range Images Using Labeled Data from Sensors with Higher Resolution—0
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars—0
On the Interaction between Autonomous Mobility on Demand Systems and Power Distribution Networks -- An Optimal Power Flow ApproachCode0
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