Large-scale nonlinear facial image classification based on approximate kernel Extreme Learning Machine

Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas
2015 2015 IEEE International Conference on Image Processing (ICIP)  
In this paper, we propose a scheme that can be used in largescale nonlinear facial image classification problems. An approximate solution of the kernel Extreme Learning Machine classifier is formulated and evaluated. Experiments on two publicly available facial image datasets using two popular facial image representations illustrate the effectiveness and efficiency of the proposed approach. The proposed Approximate Kernel Extreme Learning Machine classifier is able to scale well in both time
more » ... memory, while achieving good generalization performance. Specifically, it is shown that it outperforms the standard ELM approach for the same time and memory requirements. Compared to the original kernel ELM approach, it achieves similar (or better) performance, while scaling well in both time and memory with respect to the training set cardinality.
doi:10.1109/icip.2015.7351242 dblp:conf/icip/IosifidisTP15a fatcat:f2vnsikguraynfwrmzx4qsubd4