130 citations · 205 across the 3 of their papers we have counts for
8 papers
Self-paced Resistance Learning against Overfitting on Noisy Labels
Xiaoshuang Shi, Zhenhua Guo, Kang Li +2
Noisy labels composed of correct and corrupted ones are pervasive in practice. They might significantly deteriorate the performance of convolutional neural networks (CNNs), because…
Cluster Activation Mapping with Applications to Medical Imaging
Sarah Ryan, Nichole Carlson, Harris Butler +3
An open question in deep clustering is how to understand what in the image is creating the cluster assignments. This visual understanding is essential to be able to trust the resul…
A Scalable Optimization Mechanism for Pairwise based Discrete Hashing
Xiaoshuang Shi, Fuyong Xing, Zizhao Zhang +3
Maintaining the pair similarity relationship among originally high-dimensional data into a low-dimensional binary space is a popular strategy to learn binary codes. One simiple and…
Pancreas Segmentation in CT and MRI Images via Domain Specific Network Designing and Recurrent Neural Contextual Learning
Jinzheng Cai, Le Lu, Fuyong Xing +1
Automatic pancreas segmentation in radiology images, eg., computed tomography (CT) and magnetic resonance imaging (MRI), is frequently required by computer-aided screening, diagnos…
Recent Advances in the Applications of Convolutional Neural Networks to Medical Image Contour Detection
Zizhao Zhang, Fuyong Xing, Hai Su +2
The fast growing deep learning technologies have become the main solution of many machine learning problems for medical image analysis. Deep convolution neural networks (CNNs), as…
Improving Deep Pancreas Segmentation in CT and MRI Images via Recurrent Neural Contextual Learning and Direct Loss Function
Jinzheng Cai, Le Lu, Yuanpu Xie +2
Deep neural networks have demonstrated very promising performance on accurate segmentation of challenging organs (e.g., pancreas) in abdominal CT and MRI scans. The current deep le…