The Comparison of Support Vector Machine and Softmax Classifier in Butterflies Recognition Problem
碩士 === 國立中央大學 === 數學系 === 107 === The purpose of this thesis is to explore the training resul ts of two deep learning models :(1) Support Vector Machine ;(2) Softmax Classifier in image recognition, and study the influence of loss functions on the iterative parameters . We demonstrate the results of...
Main Authors: | Kuan-Ting Chen, 陳冠廷 |
---|---|
Other Authors: | Meng-Kai Hong |
Format: | Others |
Language: | zh-TW |
Published: |
2018
|
Online Access: | http://ndltd.ncl.edu.tw/handle/93g7ka |
Similar Items
-
Hand Detection Using Cascade of Softmax Classifiers
by: Yan-Guo Zhao, et al.
Published: (2018-01-01) -
Photoplethysmography Biometric Recognition Model Based on Sparse Softmax Vector and k-Nearest Neighbor
by: Junfeng Yang, et al.
Published: (2020-01-01) -
Tuned Support Vector Machine Classifier for Pedestrian Recognition in Urban Traffic
by: Henry A Roncancio, et al.
Published: (2012-12-01) -
Performance comparison of support vector machine and relevance vector machine classifiers for functional MRI data
by: Perez, Daniel Antonio
Published: (2010) -
Improved softmax loss for deep learning-based face and expression recognition
by: Jiancan Zhou, et al.
Published: (2019-09-01)