Search Results for author: Yunpeng Wang

Found 6 papers, 1 papers with code

Metastatic Cancer Image Classification Based On Deep Learning Method

no code implementations13 Nov 2020 Guanwen Qiu, Xiaobing Yu, Baolin Sun, Yunpeng Wang, Lipei Zhang

Using histopathological images to automatically classify cancer is a difficult task for accurately detecting cancer, especially to identify metastatic cancer in small image patches obtained from larger digital pathology scans.

Classification General Classification +1

AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?

1 code implementation28 Oct 2020 Jun Ma, Yao Zhang, Song Gu, Cheng Zhu, Cheng Ge, Yichi Zhang, Xingle An, Congcong Wang, Qiyuan Wang, Xin Liu, Shucheng Cao, Qi Zhang, Shangqing Liu, Yunpeng Wang, Yuhui Li, Jian He, Xiaoping Yang

With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets.

Continual Learning Pancreas Segmentation

SFE-GACN: A Novel Unknown Attack Detection Method Using Intra Categories Generation in Embedding Space

no code implementations12 Apr 2020 Ao Liu, Yunpeng Wang, Tao Li

In this paper, we propose a novel unknown attack detection method based on Intra Categories Generation in Embedding Space, namely SFE-GACN, which might be the solution of few-shot problem.

Data Augmentation Intrusion Detection

How Distance Transform Maps Boost Segmentation CNNs: An Empirical Study

no code implementations MIDL 2019 Jun Ma, Zhan Wei, Yiwen Zhang, Yixin Wang, Rongfei Lv, Cheng Zhu, Gaoxiang Chen, Jianan Liu, Chao Peng, Lei Wang, Yunpeng Wang, Jianan Chen

The \emph{second contribution} is that we systematically evaluated five benchmark methods on two representative public datasets.

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

no code implementations7 May 2017 Haiyang Yu, Zhihai Wu, Shuqin Wang, Yunpeng Wang, Xiaolei Ma

Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network.

motion prediction Traffic Prediction

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

no code implementations16 Jan 2017 Xiaolei Ma, Zhuang Dai, Zhengbing He, Jihui Na, Yong Wang, Yunpeng Wang

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy.

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