Shanshan Wang

Cross Domain Adaptation by Learning Partially Shared Classifiers and Weighting Source Data Points in the Shared Subspaces

2016 · ArXiv.org

Transfer learning is a problem defined over two domains. These two domains share the same feature space and class label space, but have significantly different distributions. One domain has sufficient labels, named as source domain, …

AUNet: attention-guided dense-upsampling networks for breast mass segmentation in whole mammograms

2019 · Physics in Medicine and Biology

Mammography is one of the most commonly applied tools for early breast cancer screening. Automatic segmentation of breast masses in mammograms is essential but challenging due to the low signal-to-noise ratio and the wide variety …

Residual CNN-Based Transceiver With Attention-Aided GAN for Unknown Channels

2025 · IEEE Transactions on Cognitive Communications and Networking

Intelligent transceivers and wireless channels form an autoencoder (AE) structure, demonstrating a significant improvement in communication performance through end-to-end (E2E) learning. Recently, when the wireless channel is unknown, a residual generative adversarial network (GAN) has …

Graph Convolutional Mixture-of-Experts Learner Network for Long-Tailed Domain Generalization

2025 · IEEE Transactions on Circuits and Systems for Video Technology

The goal of single domain generalization is to use data from a single domain (source domain) to train a model, which is then deployed over several unknown domains for testing (target domains). This study introduces …