@article{MAKHILLAJIT20076115484,
    title = {ANN and SVM Based Image Classification Using Wavelet Decomposition},
    journal = {Asian Journal of Information Technology},
    volume = {6},
    number = {11},
    pages = {1174-1180},
    year = {2007},
    issn = {1682-3915},
    doi = {ajit.2007.1174.1180},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2007.1174.1180},
    author = {V. Devendran,Amitabh Wahi and},
    keywords = {Artificial neural networks,image classification,multi-level wavelet decomposition,support vector machines},
    abstract = {This study discusses the comparative study of ANN and SVM in the classification problem domain. We are classifying the static images into two categories i.e., images with cars and images with no cars. This is tested without any segmentation processes. Feed forward neural networks with backpropagation algorithm are used for paradigm of ANN. On the other hand, support vector machine with radial basis kernel function with p = 5 is used for the same image classification problem. Comparative results show that the classification rate of SVM is far better than the classification rate of ANN. Features are extracted from the static images using Multi-level wavelet decomposition method. The performance of ANN and SVM is tested in 5 different levels of decomposition. This research is carried out using real world data set.}
    }