17 citations · 18 across the 3 of their papers we have counts for
4 papers
Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision
Hoel Kervadec, Jose Dolz, Shanshan Wang +2
We propose a novel weakly supervised learning segmentation based on several global constraints derived from box annotations. Particularly, we leverage a classical tightness prior t…
Manifold Criterion Guided Transfer Learning via Intermediate Domain Generation
Lei Zhang, Shanshan Wang, Guang-Bin Huang +3
In many practical transfer learning scenarios, the feature distribution is different across the source and target domains (i.e. non-i.i.d.). Maximum mean discrepancy (MMD), as a do…
Low-Latency Deep Clustering For Speech Separation
Shanshan Wang, Gaurav Naithani, Tuomas Virtanen
This paper proposes a low algorithmic latency adaptation of the deep clustering approach to speaker-independent speech separation. It consists of three parts: a) the usage of long-…
Cross Domain Adaptation by Learning Partially Shared Classifiers and Weighting Source Data Points in the Shared Subspaces
Hongqi Wang, Anfeng Xu, Shanshan Wang +1
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 d…