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Robust object detection under harsh autonomous‐driving environments

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-01252-6_24openalex-snapshot

Receptive Field Block Net for Accurate and Fast Object Detection

inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot

Microsoft COCO: Common Objects in Context

inferredcites →https://doi.org/10.1007/978-3-319-24574-4_46openalex-snapshot

Robust Cell Detection and Segmentation in Histopathological Images Using Sparse Reconstruction and Stacked Denoising Autoencoders

inferredcites →https://doi.org/10.1007/978-3-319-46493-0_38openalex-snapshot

Identity Mappings in Deep Residual Networks

inferredcites →https://doi.org/10.1016/j.patrec.2019.11.004openalex-snapshot

Moving object detection under different weather conditions using full-spectrum light sources

inferredcites →https://doi.org/10.1109/access.2018.2807385openalex-snapshot

Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey

inferredcites →https://doi.org/10.1109/cvpr.2016.308openalex-snapshot

Rethinking the Inception Architecture for Computer Vision

inferredcites →https://doi.org/10.1109/cvpr.2017.683openalex-snapshot

Residual Attention Network for Image Classification

inferredcites →https://doi.org/10.1109/cvpr.2018.00062openalex-snapshot

Scale-Transferrable Object Detection

inferredcites →https://doi.org/10.1109/cvpr.2018.00175openalex-snapshot

Robust Physical-World Attacks on Deep Learning Visual Classification

inferredcites →https://doi.org/10.1109/cvpr.2018.00442openalex-snapshot

Single-Shot Refinement Neural Network for Object Detection

inferredcites →https://doi.org/10.1109/cvpr42600.2020.01170openalex-snapshot

Seeing Through Fog Without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather

inferredcites →https://doi.org/10.1109/iccv.2017.322openalex-snapshot

Mask R-CNN

inferredcites →https://doi.org/10.1109/iccv.2017.593openalex-snapshot

Soft-NMS — Improving Object Detection with One Line of Code

inferredcites →https://doi.org/10.1109/iccv.2017.89openalex-snapshot

Deformable Convolutional Networks

inferredcites →https://doi.org/10.1109/iccv.2019.00059openalex-snapshot

Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving

inferredcites →https://doi.org/10.1109/iccv.2019.00972openalex-snapshot

FCOS: Fully Convolutional One-Stage Object Detection

inferredcites →https://doi.org/10.1109/iccv.2019.00984openalex-snapshot

AutoFocus: Efficient Multi-Scale Inference

inferredcites →https://doi.org/10.1109/icess.2019.8782514openalex-snapshot

Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models

inferredcites →https://doi.org/10.1109/lsens.2018.2860990openalex-snapshot

Temperature Effect on the Linearity Performance of a CMOS Image Sensor

inferredcites →https://doi.org/10.1109/tnnls.2018.2886017openalex-snapshot

Adversarial Examples: Attacks and Defenses for Deep Learning

inferredcites →https://doi.org/10.1177/0278364913491297openalex-snapshot

Vision meets robotics: The KITTI dataset

inferredcites →https://doi.org/10.12792/icisip2019.002openalex-snapshot

Object Detection for Autonomous Driving

inferredcites →https://doi.org/10.1609/aaai.v33i01.33019259openalex-snapshot

M2Det: A Single-Shot Object Detector Based on Multi-Level Feature Pyramid Network

inferredcites →https://doi.org/10.3390/s20020349openalex-snapshot

Analysis of the Influence of Foggy Weather Environment on the Detection Effect of Machine Vision Obstacles

inferredcites →https://doi.org/10.48550/arxiv.1705.03387openalex-snapshot

Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN

inferredcites →https://doi.org/10.48550/arxiv.1705.07204openalex-snapshot

Ensemble Adversarial Training: Attacks and Defenses

inferredcites →https://doi.org/10.48550/arxiv.1710.10571openalex-snapshot

Certifying Some Distributional Robustness with Principled Adversarial Training

inferredcites →https://doi.org/10.48550/arxiv.1907.07484openalex-snapshot

Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

inferredcites →https://doi.org/10.52202/085713openalex-snapshot

Advances in Neural Information Processing Systems 19

inferredcites →https://doi.org/10.5555/1756006.1953039openalex-snapshot

Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Interpretable Machine Learning: A Comprehensive Review of Foundations, Methods, and the Path Forward

inferred← citeshttps://doi.org/10.1007/978-3-030-79150-6_21openalex-snapshot

Robustness Testing of AI Systems: A Case Study for Traffic Sign Recognition

inferred← citeshttps://doi.org/10.1007/978-3-031-49018-7_39openalex-snapshot

Condition Invariance for Autonomous Driving by Adversarial Learning

inferred← citeshttps://doi.org/10.1007/978-981-96-6975-2_9openalex-snapshot

Multi-level Critical Transformation Robustness Evaluation of Object Detection Models

inferred← citeshttps://doi.org/10.1007/978-981-97-3466-5_9openalex-snapshot

Real-Time Multi-objects Detection Using YOLOv7 for Advanced Driving Assistant Systems

inferred← citeshttps://doi.org/10.1007/s11042-023-15981-yopenalex-snapshot

A systematic review of object detection from images using deep learning

inferred← citeshttps://doi.org/10.1007/s11760-024-03068-6openalex-snapshot

Yolov4-based hybrid feature enhancement network with robust object detection under adverse weather conditions

inferred← citeshttps://doi.org/10.1016/j.compeleceng.2024.109643openalex-snapshot

Security, privacy, and robustness for trustworthy AI systems: A review

inferred← citeshttps://doi.org/10.1016/j.engappai.2025.113526openalex-snapshot

Robust traffic sign detection in real-world harsh conditions: A pioneering benchmark dataset and attention-based methodology

inferred← citeshttps://doi.org/10.1016/j.eswa.2025.128098openalex-snapshot

Deep learning methods for autonomous driving scene understanding tasks: A review

inferred← citeshttps://doi.org/10.1016/j.neucom.2025.130775openalex-snapshot

A progressive sampling method for object detection performance surface based on Gaussian process multi-kernel fusion

inferred← citeshttps://doi.org/10.1049/ipr2.12496openalex-snapshot

A deep grouping fusion neural network for multimedia content understanding

inferred← citeshttps://doi.org/10.1049/ipr2.13110openalex-snapshot

DAF‐Retinex: Preserve the image detailed features and restore the reflected image

inferred← citeshttps://doi.org/10.1049/itr2.70017openalex-snapshot

Towards a Data‐Driven Digital Twin AI‐Based Architecture for Self‐Driving Vehicles

inferred← citeshttps://doi.org/10.1109/access.2023.3258626openalex-snapshot

Robust Object Detection Against Multi-Type Corruption Without Catastrophic Forgetting During Adversarial Training Under Harsh Autonomous-Driving Environments

inferred← citeshttps://doi.org/10.1109/emergin67762.2025.11450850openalex-snapshot

Advancements In Object Detection for Transportation System: An Ai-Driven Comprehensive Review

inferred← citeshttps://doi.org/10.1109/icdt57929.2023.10151288openalex-snapshot

Generative Adversarial Networks to Improve the Nature of Training in Autonomous Vehicles

inferred← citeshttps://doi.org/10.1109/tits.2024.3468038openalex-snapshot

SpikeTOD: A Biologically Interpretable Spike-Driven Object Detection in Challenging Traffic Scenarios

inferred← citeshttps://doi.org/10.1109/tiv.2024.3351271openalex-snapshot

Efficient and Robust Object Detection Against Multi-Type Corruption Using Complete Edge Based on Lightweight Parameter Isolation

inferred← citeshttps://doi.org/10.1177/09544070251337211openalex-snapshot

Blockchain and AI for improved data management and traffic safety in the internet of vehicles: A systematic review

inferred← citeshttps://doi.org/10.3233/ida-230075openalex-snapshot

CCTSDB dataset enhancement based on a cross-augmentation method for image datasets

inferred← citeshttps://doi.org/10.3390/sym16030356openalex-snapshot

A Low-Latency Noise-Aware Tone Mapping Operator for Hardware Implementation with a Locally Weighted Guided Filter

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