Search Results for author: Ying Yang

Found 17 papers, 2 papers with code

An application of cascaded 3D fully convolutional networks for medical image segmentation

1 code implementation14 Mar 2018 Holger R. Roth, Hirohisa ODA, Xiangrong Zhou, Natsuki Shimizu, Ying Yang, Yuichiro Hayashi, Masahiro Oda, Michitaka Fujiwara, Kazunari Misawa, Kensaku MORI

In this work, we show that a multi-class 3D FCN trained on manually labeled CT scans of several anatomical structures (ranging from the large organs to thin vessels) can achieve competitive segmentation results, while avoiding the need for handcrafting features or training class-specific models.

3D Medical Imaging Segmentation Image Segmentation +2

High-order structure preserving graph neural network for few-shot learning

1 code implementation29 May 2020 Guangfeng Lin, Ying Yang, Yindi Fan, Xiaobing Kang, Kaiyang Liao, Fan Zhao

Most existing methods try to model the similarity relationship of the samples in the intra tasks, and generalize the model to identify the new categories.

Few-Shot Learning Vocal Bursts Intensity Prediction

A state-space model of cross-region dynamic connectivity in MEG/EEG

no code implementations NeurIPS 2016 Ying Yang, Elissa Aminoff, Michael Tarr, Kass E. Robert

The model treats the mean activity in individual ROIs as the state variable, and describes non-stationary dynamic dependence across ROIs using time-varying auto-regression.

EEG Electroencephalogram (EEG)

A new 2D auxetic CN2 nanostructure with high energy density and mechanical strength

no code implementations14 Dec 2020 Qun Wei, Ying Yang, Alexander Gavrilov, Xihong Peng

The modulus in the zigzag direction is predicted to be 340 N/m, stiffer than h-BN and penta-CN2 sheets and comparable to graphene.

Band Gap Materials Science Computational Physics

Unsupervised Spatial-spectral Network Learning for Hyperspectral Compressive Snapshot Reconstruction

no code implementations18 Dec 2020 Yubao Sun, Ying Yang, Qingshan Liu, Mohan Kankanhalli

Hyperspectral compressive imaging takes advantage of compressive sensing theory to achieve coded aperture snapshot measurement without temporal scanning, and the entire three-dimensional spatial-spectral data is captured by a two-dimensional projection during a single integration period.

Compressive Sensing

Simultaneous reconstruction and displacement estimation for spectral-domain optical coherence elastography

no code implementations2 Aug 2021 Jonathan H. Mason, Yvonne Reinwald, Ying Yang, Sarah Waters, Alicia El Haj, Pierre O. Bagnaninchi

Optical coherence elastography allows the characterization of the mechanical properties of tissues, and can be performed through estimating local displacement maps from subsequent acquisitions of a sample under different loads.

Denoising

Model-based iterative reconstruction for spectral-domain optical coherence tomography

no code implementations2 Aug 2021 Jonathan H. Mason, Yvonne Reinwald, Ying Yang, Sarah Waters, Alicia El Haj, Pierre O. Bagnaninchi

Spectral domain optical coherence tomography (OCT) offers high resolution multidimensional imaging, but generally suffers from defocussing, intensity falloff and shot noise, causing artifacts and image degradation along the imaging depth.

Policy Evaluation for Temporal and/or Spatial Dependent Experiments

no code implementations22 Feb 2022 Shikai Luo, Ying Yang, Chengchun Shi, Fang Yao, Jieping Ye, Hongtu Zhu

The aim of this paper is to establish a causal link between the policies implemented by technology companies and the outcomes they yield within intricate temporal and/or spatial dependent experiments.

Marketing

Single-pixel imaging based on weight sort of the Hadamard basis

no code implementations9 Mar 2022 Wen-Kai Yu, Chong Cao, Ying Yang, Ning Wei, Shuo-Fei Wang, Chen-Xi Zhu

Single-pixel imaging (SPI) is very popular in subsampling applications, but the random measurement matrices it typically uses will lead to measurement blindness as well as difficulties in calculation and storage, and will also limit the further reduction in sampling rate.

Secondary complementary balancing compressive imaging with a free-space balanced amplified photodetector

no code implementations18 Mar 2022 Wen-Kai Yu, Ying Yang, Jin-Rui Liu, Ning Wei, Shuo-Fei Wang

Single-pixel imaging (SPI) has attracted widespread attention because it generally uses a non-pixelated photodetector and a digital micromirror device (DMD) to acquire the object image.

Image Restoration

Retinex Image Enhancement Based on Sequential Decomposition With a Plug-and-Play Framework

no code implementations11 Oct 2022 Tingting Wu, Wenna Wu, Ying Yang, Feng-Lei Fan, Tieyong Zeng

In this paper, using a sequential Retinex decomposition strategy, we design a plug-and-play framework based on the Retinex theory for simultaneously image enhancement and noise removal.

Denoising Low-Light Image Enhancement

Counterfactual Graph Transformer for Traffic Flow Prediction

no code implementations1 Aug 2023 Ying Yang, Kai Du, Xingyuan Dai, Jianwu Fang

We design a perturbation mask generator over input sensor features at the time dimension and the graph structure on the graph transformer module to obtain spatial and temporal counterfactual explanations.

counterfactual

DomainVerse: A Benchmark Towards Real-World Distribution Shifts For Tuning-Free Adaptive Domain Generalization

no code implementations5 Mar 2024 Feng Hou, Jin Yuan, Ying Yang, Yang Liu, Yang Zhang, Cheng Zhong, Zhongchao shi, Jianping Fan, Yong Rui, Zhiqiang He

With the recent advance of vision-language models (VLMs), viewed as natural source models, the cross-domain task changes to directly adapt the pre-trained source model to arbitrary target domains equipped with prior domain knowledge, and we name this task Adaptive Domain Generalization (ADG).

Domain Generalization

An Analysis of Switchback Designs in Reinforcement Learning

no code implementations26 Mar 2024 Qianglin Wen, Chengchun Shi, Ying Yang, Niansheng Tang, Hongtu Zhu

Our aim is to thoroughly evaluate the effects of these designs on the accuracy of their resulting average treatment effect (ATE) estimators.

reinforcement-learning

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