Mixtures of probabilistic principal component analyzers
Neural Computation
Pattern Recognition with Fuzzy Objective Function Algorithms
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Benchmarking Least Squares Support Vector Machine Classifiers
Machine Learning
Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications
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Postsupervised hard c-means classifier
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
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The most prevailing approach now for parking lot vacancy detecting system is to use sensor-based techniques. The main impediments to the camera-based system in applying to parking lots on rooftop and outside building are the glaring sun light and dark shadows in the daytime, and low-light intensity and back-lighting in the nighttime. To date, no camera-based detecting systems for outdoor parking lots have been in practical use. A few engineering firms provide the camera-based system, which is only for underground and indoor parking lots. This paper reports on the new camera based system called ParkLotD for detecting vacancy/occupancy in parking lots. ParkLotD uses a classifier based on fuzzy c-means (FCM) clustering and hyper-parameter tuning by particle swarm optimization (PSO). The test result of the detection error rate for the indoor multi-story parking lot has improved by an order of magnitude compared to the current system based on the edge detection approach. ParkLotD demonstrates high detection performance and enables the camera-based system to achieve the practical use in outdoor parking lots.