177 citations · 305 across the 11 of their papers we have counts for
11 papers
The QXS-SAROPT Dataset for Deep Learning in SAR-Optical Data Fusion
Meiyu Huang, Yao Xu, Lixin Qian +6
Deep learning techniques have made an increasing impact on the field of remote sensing. However, deep neural networks based fusion of multimodal data from different remote sensors…
Boosting ship detection in SAR images with complementary pretraining techniques
Wei Bao, Meiyu Huang, Yaqin Zhang +3
Deep learning methods have made significant progress in ship detection in synthetic aperture radar (SAR) images. The pretraining technique is usually adopted to support deep neural…
Training few-shot classification via the perspective of minibatch and pretraining
Meiyu Huang, Xueshuang Xiang, Yao Xu
Few-shot classification is a challenging task which aims to formulate the ability of humans to learn concepts from limited prior data and has drawn considerable attention in machin…
Transfer Learning with Dynamic Adversarial Adaptation Network
Chaohui Yu, Jindong Wang, Yiqiang Chen +1
The recent advances in deep transfer learning reveal that adversarial learning can be embedded into deep networks to learn more transferable features to reduce the distribution dis…
Transfer Learning with Dynamic Distribution Adaptation
Jindong Wang, Yiqiang Chen, Wenjie Feng +3
Transfer learning aims to learn robust classifiers for the target domain by leveraging knowledge from a source domain. Since the source and the target domains are usually from diff…
Task-Driven Common Representation Learning via Bridge Neural Network
Yao Xu, Xueshuang Xiang, Meiyu Huang
This paper introduces a novel deep learning based method, named bridge neural network (BNN) to dig the potential relationship between two given data sources task by task. The propo…
Easy Transfer Learning By Exploiting Intra-domain Structures
Jindong Wang, Yiqiang Chen, Han Yu +2
Transfer learning aims at transferring knowledge from a well-labeled domain to a similar but different domain with limited or no labels. Unfortunately, existing learning-based meth…
Stochastic Model Pruning via Weight Dropping Away and Back
Haipeng Jia, Xueshuang Xiang, Da Fan +3
Deep neural networks have dramatically achieved great success on a variety of challenging tasks. However, most successful DNNs have an extremely complex structure, leading to exten…
Deep Transfer Learning for Cross-domain Activity Recognition
Jindong Wang, Vincent W. Zheng, Yiqiang Chen +1
Human activity recognition plays an important role in people's daily life. However, it is often expensive and time-consuming to acquire sufficient labeled activity data. To solve t…
Visual Domain Adaptation with Manifold Embedded Distribution Alignment
Jindong Wang, Wenjie Feng, Yiqiang Chen +3
Visual domain adaptation aims to learn robust classifiers for the target domain by leveraging knowledge from a source domain. Existing methods either attempt to align the cross-dom…
Cross-position Activity Recognition with Stratified Transfer Learning
Yiqiang Chen, Jindong Wang, Meiyu Huang +1
Human activity recognition aims to recognize the activities of daily living by utilizing the sensors on different body parts. However, when the labeled data from a certain body pos…