@inproceedings{7fc49ce36c7a4adf99b5e8dd18cd338e,
title = "Image classification using appearance based features",
abstract = "In this paper, a small set of features based on local appearance and texture is applied to the task of image recognition and classification. These features are used to train and subsequently test three different machine learning techniques, namely k-Nearest Neighbors (K-NN), Support Vector Machines (SVM) and Ensemble Learning (Bagging). A case study on a publicly available object classification dataset was conductor from which it was concluded that, while simple, the proposed approach was able to produce extremely high classification accuracies.",
keywords = "Edge Detection, Features Extraction, Image Classification, Object Recognition, Texture Analysis",
author = "Dina Masri and Zeyar Aung and Woon, \{Wei Lee\}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 11th International Conference on Innovations in Information Technology, IIT 2015 ; Conference date: 01-11-2015 Through 03-11-2015",
year = "2016",
month = jan,
day = "12",
doi = "10.1109/INNOVATIONS.2015.7381527",
language = "British English",
series = "Proceedings - 2015 11th International Conference on Innovations in Information Technology, IIT 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "128--133",
editor = "Leila Ismail",
booktitle = "Proceedings - 2015 11th International Conference on Innovations in Information Technology, IIT 2015",
address = "United States",
}