Mixture separability loss in a deep convolutional network for image classification-Reference-Cited by-同舟云学术

Mixture separability loss in a deep convolutional network for image classification

Published:2019-01 Issue:1 Volume:13 Page:135-141
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Do Trung Dung¹,Jin Cheng‐Bin¹^ORCID,Nguyen Van Huan²,Kim Hakil¹^ORCID

Affiliation:

1. Department of Information and Communication EngineeringInha University22212IncheonRepublic of Korea

2. Faculty of Information TechnologyTon Duc Thang UniversityHo Chi Minh CityVietnam

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2018.5613

Reference33 articles.

1. 2012 Conf. Neural Information Processing Systems Lake Tahoe Nevada USA A. Krizhevsky I. Sutskever G.E. Hinton Imagenet classification with deep convolutional neural networks 1097 1105

2. 2015 Int. Conf. Learning Representation San Diego USA K. Simonyan A. Zisserman Very deep convolutional networks for large‐scale image recognition

3. 2017 IEEE Conf. Computer Vision and Pattern Recognition Honolulu HI USA F. Chollet Xception: deep learning with depthwise separable convolutions 1800 1807

4. 2016 IEEE Conf. Computer Vision and Pattern Recognition Las Vegas NV USA C. Szegedy V. Vanhoucke S. Ioffe Rethinking the inception architecture for computer vision 2818 2826

5. 2017 Association for the Advancement of Artificial Intelligence (AAAI) San Francisco California USA C. Szegedy S. Ioffe V. Vanhoucke Inception‐v4 inception‐resnet and the impact of residual connections on learning 4278 4284

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Improved Neural Network Classifier Using Fuzzy Nearest Neighbor Partitioning Method;International Journal of Fuzzy Systems;2019-09-04