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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 201–250 of 514 papers

TitleStatusHype
Dataset Curation Beyond Accuracy—0
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars—0
Image segmentation of cross-country scenes captured in IR spectrum—0
CrowdDriven: A New Challenging Dataset for Outdoor Visual Localization—0
Applying adversarial networks to increase the data efficiency and reliability of Self-Driving Cars—0
AdvMS: A Multi-source Multi-cost Defense Against Adversarial Attacks—0
Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study—0
Cross-Layer Performance Evaluation of C-V2X—0
Application of Neuroevolution in Autonomous Cars—0
Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving—0
High Resolution Millimeter Wave Imaging For Self-Driving Cars—0
CPIPS: Learning to Preserve Perceptual Distances in End-to-End Image Compression—0
A Novel Graph based Trajectory Predictor with Pseudo Oracle—0
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective—0
ACDC: The Adverse Conditions Dataset with Correspondences for Robust Semantic Driving Scene Perception—0
Gray-box Adversarial Attack of Deep Reinforcement Learning-based Trading Agents—0
Gradient-Free Adversarial Training Against Image Corruption for Learning-based Steering—0
Continual Hyperbolic Learning of Instances and Classes—0
Anomalous State Sequence Modeling to Enhance Safety in Reinforcement Learning—0
GOAT: GPU Outsourcing of Deep Learning Training With Asynchronous Probabilistic Integrity Verification Inside Trusted Execution Environment—0
GLADAS: Gesture Learning for Advanced Driver Assistance Systems—0
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space—0
GINN: Fast GPU-TEE Based Integrity for Neural Network Training—0
Context Aware Road-user Importance Estimation (iCARE)—0
Adversarial Attacks and Defense on Texts: A Survey—0
How far should self-driving cars see? Effect of observation range on vehicle self-localization—0
Human Trajectory Forecasting with Explainable Behavioral Uncertainty—0
Human Trajectory Prediction With Momentary Observation—0
Hybrid Deep Reinforcement Learning and Planning for Safe and Comfortable Automated Driving—0
Hybrid Scene Compression for Visual Localization—0
Hyperbolic Uncertainty Aware Semantic Segmentation—0
Image-based OoD-Detector Principles on Graph-based Input Data in Human Action Recognition—0
Synthetic Observational Health Data with GANs: from slow adoption to a boom in medical research and ultimately digital twins?—0
Conditional Driving from Natural Language Instructions—0
Importance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training—0
Importance Filtering with Risk Models for Complex Driving Situations—0
Improved LiDAR Odometry and Mapping using Deep Semantic Segmentation and Novel Outliers Detection—0
Improving and Assessing Anomaly Detectors for Large-Scale Settings—0
An NCAP-like Safety Indicator for Self-Driving Cars—0
Towards Long-Range 3D Object Detection for Autonomous Vehicles—0
CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Cars—0
Inferring Temporal Logic Properties from Data using Boosted Decision Trees—0
Fully Dynamic Inference with Deep Neural Networks—0
Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Images—0
Interaction Detection Between Vehicles and Vulnerable Road Users: A Deep Generative Approach with Attention—0
Interpretable Learning for Self-Driving Cars by Visualizing Causal Attention—0
Computer Vision based Accident Detection for Autonomous Vehicles—0
Adversarial Attack Attribution: Discovering Attributable Signals in Adversarial ML Attacks—0
Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry—0
FRSign: A Large-Scale Traffic Light Dataset for Autonomous Trains—0
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