Search Results for author: Tao Peng

Found 17 papers, 6 papers with code

Document-level Relation Extraction with Relation Correlations

1 code implementation20 Dec 2022 Ridong Han, Tao Peng, Benyou Wang, Lu Liu, Xiang Wan

Document-level relation extraction faces two overlooked challenges: long-tail problem and multi-label problem.

Document-level Relation Extraction Relation

Ghost translation

no code implementations29 Sep 2022 Wenhan Ren, Xiaoyu Nie, Tao Peng, Marlan O. Scully

This translation mechanism opens a new direction for DNN-assisted ghost imaging and can be used in various computational imaging scenarios.

Translation

Recurrence-free Survival Prediction under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers

1 code implementation22 Sep 2022 Kai Wang, Yunxiang Li, Michael Dohopolski, Tao Peng, Weiguo Lu, You Zhang, Jing Wang

For Head and Neck Cancers (HNC) patient management, automatic gross tumor volume (GTV) segmentation and accurate pre-treatment cancer recurrence prediction are of great importance to assist physicians in designing personalized management plans, which have the potential to improve the treatment outcome and quality of life for HNC patients.

Management Segmentation +2

Retinex-qDPC: automatic background rectified quantitative differential phase contrast imaging

no code implementations21 Jul 2022 Shuhe Zhang, Tao Peng, Zeyu Ke, Han Yang, Tos T. J. M. Berendschot, Jinhua Zhou

To tackle the mismatch of background and increases the experimental robustness, we propose the Retinex-qDPC in which we use the images edge features as data fidelity term yielding L2-Retinex-qDPC and L1-Retinex-qDPC for high background-robustness qDPC reconstruction.

Deep-learned speckle pattern and its application to ghost imaging

no code implementations25 Dec 2021 Xiaoyu Nie, Haotian Song, Wenhan Ren, Xingchen Zhao, Zhedong Zhang, Tao Peng, Marlan O. Scully

Our method, therefore, outperforms the other techniques for ghost imaging, particularly its ability to retrieve high-quality images with extremely low sampling ratios.

Graph neural network-based fault diagnosis: a review

no code implementations16 Nov 2021 Zhiwen Chen, Jiamin Xu, Cesare Alippi, Steven X. Ding, Yuri Shardt, Tao Peng, Chunhua Yang

Graph neural network (GNN)-based fault diagnosis (FD) has received increasing attention in recent years, due to the fact that data coming from several application domains can be advantageously represented as graphs.

Graph Attention Time Series +1

RSS-based Multiple Sources Localization with Unknown Log-normal Shadow Fading

no code implementations20 Oct 2021 Yueyan Chu, Wenbin Guo, Kangyong You, Lei Zhao, Tao Peng, Wenbo Wang

Then we utilize the K-means clustering method to obtain the rough locations of the off-grid sources as the initial feasible point of the ML estimator.

Distantly Supervised Relation Extraction via Recursive Hierarchy-Interactive Attention and Entity-Order Perception

1 code implementation18 May 2021 Ridong Han, Tao Peng, Jiayu Han, Hai Cui, Lu Liu

Based on the above, in this paper, we design a novel Recursive Hierarchy-Interactive Attention network (RHIA) to further handle long-tail relations, which models the heuristic effect between relation levels.

Relation Relation Extraction +1

Superresolving second-order correlation imaging using synthesized colored noise speckles

no code implementations11 Feb 2021 Zheng Li, Xiaoyu Nie, Fan Yang, Xiangpei Liu, Dongyu Liu, Xiaolong Dong, Xingchen Zhao, Tao Peng, M. Suhail Zubairy, Marlan O. Scully

We present a novel method to synthesize non-trivial speckles that can enable superresolving second-order correlation imaging.

Optics Image and Video Processing

High order Coherence Functions and Spectral Distributions as given by the Quantum Theory of Laser Radiation

no code implementations22 Jan 2021 Tao Peng, Xingchen Zhao, Yanhua Shih, Marlan O. Scully

We propose and demonstrate a method for measuring the time evolution of the off-diagonal elements $\rho_{n, n+k}(t)$ of the reduced density matrix obtained from the quantum theory of the laser.

Optics

Non-invasive imaging of object behind strongly scattering media via cross-spectrum

no code implementations11 Dec 2020 Xingchen Zhao, Tao Peng, Zhenhuan Yi, Lida Zhang, M. Suhail Zubairy, Yanhua Shih, Marlan O. Scully

We develop a method based on the cross-spectrum of an intensity-modulated CW laser, which can extract a signal from an extremely noisy environment and image objects hidden in turbid media.

Optics Biological Physics

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