WALLACE: Weakly Supervised Learning of Deep Convolutional Neural Networks With Multiscale Evidence

WALLACE: Weakly Supervised Learning of Deep Convolutional Neural Networks With Multiscale Evidence

This paper presents WALLACE, a new framework of deep convolutional neural networks, which perform ConvNet's pyramidal feature hierarchy for weakly supervised learning. Most prior works rely on the image pyramid or network ensemble, which is both complicated and usually expensive. Instead, WALLA...

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Bibliographic Details
Main Authors: Yongsheng Liu, Wenyu Chen, Hong Qu, Tianlei Wang, Jiangzhou Ji, Kebin Miao
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Weakly supervised learning
convolutional neural networks
object localization
object classification
multi-scale features
Online Access:https://ieeexplore.ieee.org/document/8966337/

Internet

https://ieeexplore.ieee.org/document/8966337/

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