arXiv Open Access 2014

Image Classification with A Deep Network Model based on Compressive Sensing

Yufei Gan Tong Zhuo Chu He

Lihat Sumber

Abstrak

To simplify the parameter of the deep learning network, a cascaded compressive sensing model "CSNet" is implemented for image classification. Firstly, we use cascaded compressive sensing network to learn feature from the data. Secondly, CSNet generates the feature by binary hashing and block-wise histograms. Finally, a linear SVM classifier is used to classify these features. The experiments on the MNIST dataset indicate that higher classification accuracy can be obtained by this algorithm.

Topik & Kata Kunci

cs.CV

Penulis (3)

Yufei Gan

Tong Zhuo

Chu He

Format Sitasi

APA MLA BibTeX

Gan, Y., Zhuo, T., He, C. (2014). Image Classification with A Deep Network Model based on Compressive Sensing. https://arxiv.org/abs/1409.7307

Akses Cepat

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2014
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓