Search Results for author: Yingying Liu

Found 6 papers, 0 papers with code

EchoONE: Segmenting Multiple echocardiography Planes in One Model

no code implementations4 Dec 2024 Jiongtong Hu, Wei Zhuo, Jun Cheng, Yingying Liu, Wufeng Xue, Dong Ni

Effective solution for such a multi-plane segmentation (MPS) problem is highly demanded for medical images, yet has not been well investigated.

To Transmit or Not to Transmit: Optimal Sensor Schedule for Remote State Estimation of Discrete-Event Systems

no code implementations23 Nov 2023 Yingying Liu, Jin Hu, Yongxia Yang, Wei Duan

A transmission mechanism decides whether the observable information is transmitted or not, according to an information transmission policy, such that the receiver has sufficient information to satisfy the purpose of decision-making.

Decision Making

FFPN: Fourier Feature Pyramid Network for Ultrasound Image Segmentation

no code implementations26 Aug 2023 Chaoyu Chen, Xin Yang, Rusi Chen, Junxuan Yu, Liwei Du, Jian Wang, Xindi Hu, Yan Cao, Yingying Liu, Dong Ni

In this paper, we introduce a novel Fourier-anchor-based DTS framework called Fourier Feature Pyramid Network (FFPN) to address the aforementioned issues.

Image Segmentation Semantic Segmentation

Deep Learning Methods for Small Molecule Drug Discovery: A Survey

no code implementations1 Mar 2023 Wenhao Hu, Yingying Liu, Xuanyu Chen, Wenhao Chai, Hangyue Chen, Hongwei Wang, Gaoang Wang

With the development of computer-assisted techniques, research communities including biochemistry and deep learning have been devoted into the drug discovery field for over a decade.

Deep Learning Drug Discovery +3

Supervisory Control of Multi-Agent Discrete-Event Systems with Partial Observation

no code implementations19 Mar 2021 Yingying Liu, Jan Komenda, Zhiwu Li

In this paper we investigate multi-agent discrete-event systems with partial observation.

Time and Frequency Network for Human Action Detection in Videos

no code implementations8 Mar 2021 Changhai Li, Huawei Chen, Jingqing Lu, Yang Huang, Yingying Liu

Currently, spatiotemporal features are embraced by most deep learning approaches for human action detection in videos, however, they neglect the important features in frequency domain.

Action Detection

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