{"slug": "an-ensemble-based-self-taught-learning-approach-for-parking-space-classification", "title": "An Ensemble-Based Self-Taught Learning Approach for Parking Space Classification Under Limited Data", "summary": "Researchers proposed an ensemble-based self-taught learning approach using convolutional autoencoders for parking space classification, achieving 93% to 96% accuracy on the PKLot and CNRPark benchmarks under cross-dataset evaluation with limited annotated data. The method reduces annotation requirements and improves robustness across heterogeneous environments.", "body_md": "arXiv:2609.03258v1 Announce Type: new\nAbstract: Parking spot classification is a fundamental task in intelligent transportation systems, yet most deep learning approaches rely on large amounts of annotated data and exhibit limited generalization across heterogeneous environments. To address these limitations, we investigate a self-taught learning framework based on unsupervised representation learning with convolutional autoencoders. The proposed approach learns transferable visual representations from unlabeled data and reuses the learned encoders as fixed feature extractors for supervised classification with limited annotated samples in the target domain. To further enhance robustness and mitigate architectural bias, an ensemble of heterogeneous autoencoders is employed, with independent classifier heads and prediction fusion at inference time. Experiments conducted on the PKLot and CNRPark benchmarks under cross-dataset evaluation protocols show that the proposed ensemble-based strategy substantially reduces annotation requirements while improving robustness under significant domain shifts, achieving accuracies between 93\\% and 96\\% in data-constrained scenarios.", "url": "https://wpnews.pro/news/an-ensemble-based-self-taught-learning-approach-for-parking-space-classification", "canonical_source": "https://arxiv.org/abs/2609.03258", "published_at": "2026-09-04 04:00:00+00:00", "updated_at": "2026-09-04 04:24:37.978406+00:00", "lang": "en", "topics": ["machine-learning", "computer-vision"], "entities": ["PKLot", "CNRPark"], "alternates": {"html": "https://wpnews.pro/news/an-ensemble-based-self-taught-learning-approach-for-parking-space-classification", "markdown": "https://wpnews.pro/news/an-ensemble-based-self-taught-learning-approach-for-parking-space-classification.md", "text": "https://wpnews.pro/news/an-ensemble-based-self-taught-learning-approach-for-parking-space-classification.txt", "jsonld": "https://wpnews.pro/news/an-ensemble-based-self-taught-learning-approach-for-parking-space-classification.jsonld"}}