What type of study is this?

This is a Literature Review study.

August 20, 2025International Journal of Basic and Applied SciencesOpen Access

A Review of Deep Learning-Based Lane Detection Methods in Complex Environments

View Full Paper

Ask AI

Bookmark

Authors

SHShiling HuangTun Hussein Onn University of Malaysia NZNur Ariffin Mohd ZinTun Hussein Onn University of Malaysia MHMohd Hamdi Irwan HamzahTun Hussein Onn University of Malaysia

Discussion

Member takes

Implication

This review highlights deep learning methods improving lane detection accuracy in challenging environments, suggesting integrated contextual approaches.

Key Points

Deep learning enhances lane detection accuracy, improving safety in advanced driver assistance systems.
Key findings indicate that temporal-spatial fusion significantly boosts robustness against occlusions and environmental variability.
Assessment of methods like segmentation-based and parametric-based models reveals varied strengths in complex scenarios.
Future directions focus on real-time architectures and improving performance in dynamic, unstructured environments.

Cite This Study

Huang et al. (2025) studied this question.

synapsesocial.com/papers/68af5218ad7bf08b1ead993f https://doi.org/10.14419/wb7z2179

View Full Paper

Ask AI

Bookmark

August 20, 2025International Journal of Basic and Applied SciencesOpen Access

A Review of Deep Learning-Based Lane Detection Methods in Complex Environments

View Full Paper

Ask AI

Bookmark

Authors

SHShiling HuangTun Hussein Onn University of Malaysia NZNur Ariffin Mohd ZinTun Hussein Onn University of Malaysia MHMohd Hamdi Irwan HamzahTun Hussein Onn University of Malaysia

Discussion

Member takes

Implication

This review highlights deep learning methods improving lane detection accuracy in challenging environments, suggesting integrated contextual approaches.

Key Points

Deep learning enhances lane detection accuracy, improving safety in advanced driver assistance systems.
Key findings indicate that temporal-spatial fusion significantly boosts robustness against occlusions and environmental variability.
Assessment of methods like segmentation-based and parametric-based models reveals varied strengths in complex scenarios.
Future directions focus on real-time architectures and improving performance in dynamic, unstructured environments.

Cite This Study

Huang et al. (2025) studied this question.

synapsesocial.com/papers/68af5218ad7bf08b1ead993f https://doi.org/10.14419/wb7z2179

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

View Full Paper

Ask AI

Bookmark