Implicit Multidimensional Projection of Local Subspaces

1 code implementation • 7 Sep 2020 • Rongzheng Bian, Yumeng Xue, Liang Zhou, Jian Zhang, Baoquan Chen, Daniel Weiskopf, Yunhai Wang

We propose a visualization method to understand the effect of multidimensional projection on local subspaces, using implicit function differentiation.

Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model For Hyperspectral Image Classification

no code implementations • 4 Apr 2019 • Cheng Deng, Yumeng Xue, Xianglong Liu, Chao Li, DaCheng Tao

The advantages of our proposed method are threefold: 1) the network can be effectively trained using only limited labeled samples with the help of novel active learning strategies; 2) the network is flexible and scalable enough to function across various transfer situations, including cross-dataset and intra-image; 3) the learned deep joint spectral-spatial feature representation is more generic and robust than many joint spectral-spatial feature representation.

Active Learning General Classification +2