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@article{184287,
        author = {Ms. Shamina Attar and Shailashree H G and Deepak J R},
        title = {A Comprehensive Overview of Profound Learning-Based Path Discovery: Strategies, Datasets, Challenges, and Future Directions},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {835-839},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=184287},
        abstract = {Lane location is a principal component in independent driving frameworks, straightforwardly affecting vehicle localization, way arranging, and street scene understanding. In spite of significant advance, dependable path discovery remains challenging due to variables such as impediment, differing street geometries, and changing climate or lighting conditions. With the coming of profound learning, unused approaches have illustrated surprising precision and strength in extricating path highlights from complex driving situations. This paper presents a comprehensive overview of profound learning-based path location methods. We classify existing strategies into 2D and 3D approaches, assist categorizing them based on engineering methodologies, counting segmentation-based, anchor-based, and crossover systems. Also, we analyze open benchmark datasets and assessment measurements broadly embraced in the field. Comparative experiences into show execution over different scenarios are talked about, taken after by a basic examination of open challenges and potential headings for future research},
        keywords = {},
        month = {September},
        }