Comparison of Support Vector Machine and Softmax Classifiers in Computer Vision

摘要

Support Vector Machine and Softmax are two widely used linear classifiers in computer vision. Especially in the field of deep learning algorithms, the application of these two classifiers is more frequent. In addition, in the field of statistics, speech recognition, character recognition and other aspects that Support Vector Machine and Softmax also have been used. However, there are still some controversies of these two classifiers in the specific implementations. And the understanding of them comes to a significance place in deep learning process. This paper will make a comparison and analysis of the two classifiers from a holistic perspective to help the reader have a more comprehensive understanding of the two classifiers.