185 citations · 282 across the 9 of their papers we have counts for
14 papers
Learning with Feature-Dependent Label Noise: A Progressive Approach
Yikai Zhang, Songzhu Zheng, Pengxiang Wu +2
Label noise is frequently observed in real-world large-scale datasets. The noise is introduced due to a variety of reasons; it is heterogeneous and feature-dependent. Most existing…
Error-Bounded Correction of Noisy Labels
Songzhu Zheng, Pengxiang Wu, Aman Goswami +3
To collect large scale annotated data, it is inevitable to introduce label noise, i.e., incorrect class labels. To be robust against label noise, many successful methods rely on th…
Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors
Jingru Yi, Pengxiang Wu, Bo Liu +3
Oriented object detection in aerial images is a challenging task as the objects in aerial images are displayed in arbitrary directions and are usually densely packed. Current orien…
Enhanced MRI Reconstruction Network using Neural Architecture Search
Qiaoying Huang, Dong Yang, Yikun Xian +4
The accurate reconstruction of under-sampled magnetic resonance imaging (MRI) data using modern deep learning technology, requires significant effort to design the necessary comple…
PC-U Net: Learning to Jointly Reconstruct and Segment the Cardiac Walls in 3D from CT Data
Meng Ye, Qiaoying Huang, Dong Yang +4
The 3D volumetric shape of the heart's left ventricle (LV) myocardium (MYO) wall provides important information for diagnosis of cardiac disease and invasive procedure navigation.…
Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images
Hui Qu, Pengxiang Wu, Qiaoying Huang +7
Nuclei segmentation is a fundamental task in histopathology image analysis. Typically, such segmentation tasks require significant effort to manually generate accurate pixel-wise a…