Robust Vehicle Classification Based on Deep Features Learning

This paper aims to introduce a scientific Semi-Supervised Fuzzy C-Mean (SSFCM) clustering approach for passenger cars classification based on the feature learning technique. The proposed method is able classify vehicles in micro, small, middle, upper large and luxury classes. performance of algorithm analyzed compared with an unsupervised fuzzy C-means (FCM) Swiss expert dataset. Experiment results demonstrate that SSFCM has better correlation than traditional algorithm. These exhibit can reduce sensitivity FCM initial cluster centroids help labeled instances. Furthermore, improved by using resampling technique deal multi-class imbalanced problem eliminate irrelevant redundant features.