Constrained Deep Transfer Feature Learning and its Applications

09/23/2017
by   Yue Wu, et al.
0

Feature learning with deep models has achieved impressive results for both data representation and classification for various vision tasks. Deep feature learning, however, typically requires a large amount of training data, which may not be feasible for some application domains. Transfer learning can be one of the approaches to alleviate this problem by transferring data from data-rich source domain to data-scarce target domain. Existing transfer learning methods typically perform one-shot transfer learning and often ignore the specific properties that the transferred data must satisfy. To address these issues, we introduce a constrained deep transfer feature learning method to perform simultaneous transfer learning and feature learning by performing transfer learning in a progressively improving feature space iteratively in order to better narrow the gap between the target domain and the source domain for effective transfer of the data from the source domain to target domain. Furthermore, we propose to exploit the target domain knowledge and incorporate such prior knowledge as a constraint during transfer learning to ensure that the transferred data satisfies certain properties of the target domain. To demonstrate the effectiveness of the proposed constrained deep transfer feature learning method, we apply it to thermal feature learning for eye detection by transferring from the visible domain. We also applied the proposed method for cross-view facial expression recognition as a second application. The experimental results demonstrate the effectiveness of the proposed method for both applications.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 8

11/09/2018

M2M-GAN: Many-to-Many Generative Adversarial Transfer Learning for Person Re-Identification

Cross-domain transfer learning (CDTL) is an extremely challenging task f...
11/13/2017

All-Transfer Learning for Deep Neural Networks and its Application to Sepsis Classification

In this article, we propose a transfer learning method for deep neural n...
06/26/2020

Transfer Learning via ℓ_1 Regularization

Machine learning algorithms typically require abundant data under a stat...
11/25/2020

Transfer Learning for Aided Target Recognition: Comparing Deep Learning to other Machine Learning Approaches

Aided target recognition (AiTR), the problem of classifying objects from...
04/02/2019

Easy Transfer Learning By Exploiting Intra-domain Structures

Transfer learning aims at transferring knowledge from a well-labeled dom...
08/26/2020

What is being transferred in transfer learning?

One desired capability for machines is the ability to transfer their kno...
11/29/2015

The Multiverse Loss for Robust Transfer Learning

Deep learning techniques are renowned for supporting effective transfer ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.