activity
20162019
most citedImproving Deep Pancreas Segmentation in CT and MRI Images via Recurrent Neural Contextual Learning and Direct Loss Function

130 citations · 249 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL20194 cited

SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding

Baohua Sun, Lin Yang, Michael Lin +4

Language and vision are processed as two different modal in current work for image captioning. However, recent work on Super Characters method shows the effectiveness of two-dimens…

cs.NI20181 cited

Securing On-Body IoT Devices By Exploiting Creeping Wave Propagation

Wei Wang, Lin Yang, Qian Zhang +1

On-body devices are an intrinsic part of the Internet-of-Things (IoT) vision to provide human-centric services. These on-body IoT devices are largely embedded devices that lack a s…

cs.LG20171 cited

Recursive Exponential Weighting for Online Non-convex Optimization

Lin Yang, Cheng Tan, Wing Shing Wong

In this paper, we investigate the online non-convex optimization problem which generalizes the classic {online convex optimization problem by relaxing the convexity assumption on t…

cs.CV201711 cited

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…

cs.CV20173 cited

TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as Optional Semantic References

Zizhao Zhang, Pingjun Chen, Manish Sapkota +1

In this paper, we introduce the semantic knowledge of medical images from their diagnostic reports to provide an inspirational network training and an interpretable prediction mech…

cs.CV2017130 cited

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…