SOTAVerified

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 101–150 of 514 papers

TitleStatusHype
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges—0
Enhancing Autonomous Driving Safety with Collision Scenario Integration—0
Enhancing Surveillance Camera FOV Quality via Semantic Line Detection and Classification with Deep Hough Transform—0
EnSyth: A Pruning Approach to Synthesis of Deep Learning Ensembles—0
Approximate LSTMs for Time-Constrained Inference: Enabling Fast Reaction in Self-Driving Cars—0
AdvMS: A Multi-source Multi-cost Defense Against Adversarial Attacks—0
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective—0
Application of Neuroevolution in Autonomous Cars—0
Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving—0
CPIPS: Learning to Preserve Perceptual Distances in End-to-End Image Compression—0
A Novel Graph based Trajectory Predictor with Pseudo Oracle—0
Enhancing Apparent Personality Trait Analysis with Cross-Modal Embeddings—0
Cross-Layer Performance Evaluation of C-V2X—0
Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study—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
Dataset Curation Beyond Accuracy—0
Deep Bayesian Estimation for Dynamic Treatment Regimes with a Long Follow-up Time—0
Are Self-Driving Cars Secure? Evasion Attacks against Deep Neural Networks for Steering Angle Prediction—0
(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Network—0
Deep Generative Models for Vehicle Speed Trajectories—0
Deep Learning for Flight Demand Forecasting—0
Deep Learning in the Automotive Industry: Recent Advances and Application Examples—0
ArgRewrite V.2: an Annotated Argumentative Revisions Corpus—0
GAS: Generating Fast and Accurate Surrogate Models for Autonomous Vehicle Systems—0
Continual Hyperbolic Learning of Instances and Classes—0
Anomalous State Sequence Modeling to Enhance Safety in Reinforcement Learning—0
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space—0
Context Aware Road-user Importance Estimation (iCARE)—0
Adversarial Attacks and Defense on Texts: A Survey—0
Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry—0
An NCAP-like Safety Indicator for Self-Driving Cars—0
Conditional Driving from Natural Language Instructions—0
Adversarial Attack Attribution: Discovering Attributable Signals in Adversarial ML Attacks—0
CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Cars—0
Computer Vision based Accident Detection for Autonomous Vehicles—0
Enhanced Behavioral Cloning Based self-driving Car Using Transfer Learning—0
Enhanced Deep Q-Learning for 2D Self-Driving Cars: Implementation and Evaluation on a Custom Track Environment—0
Computation-Efficient and Recognition-Friendly 3D Point Cloud Privacy Protection—0
Combined Image- and World-Space Tracking in Traffic Scenes—0
Cluster Naturalistic Driving Encounters Using Deep Unsupervised Learning—0
Cloud2Edge Elastic AI Framework for Prototyping and Deployment of AI Inference Engines in Autonomous Vehicles—0
An Expert Ensemble for Detecting Anomalous Scenes, Interactions, and Behaviors in Autonomous Driving—0
A direct time-of-flight image sensor with in-pixel surface detection and dynamic vision—0
CLoCKDistill: Consistent Location-and-Context-aware Knowledge Distillation for DETRs—0
An Estimator for the Sensitivity to Perturbations of Deep Neural Networks—0
A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories—0
Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspective—0
CHAOS: A Parallelization Scheme for Training Convolutional Neural Networks on Intel Xeon Phi—0
Acceleration method for generating perception failure scenarios based on editing Markov process—0
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