Search Results for author: Cheng Zhuo

Found 19 papers, 3 papers with code

Computational and Storage Efficient Quadratic Neurons for Deep Neural Networks

no code implementations10 Jun 2023 Chuangtao Chen, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ulf Schlichtmann, Bing Li

Deep neural networks (DNNs) have been widely deployed across diverse domains such as computer vision and natural language processing.

Image Classification Semantic Segmentation

SFCNeXt: a simple fully convolutional network for effective brain age estimation with small sample size

no code implementations30 May 2023 Yu Fu, Yanyan Huang, Shunjie Dong, Yalin Wang, Tianbai Yu, Meng Niu, Cheng Zhuo

Deep neural networks (DNN) have been designed to predict the chronological age of a healthy brain from T1-weighted magnetic resonance images (T1 MRIs), and the predicted brain age could serve as a valuable biomarker for the early detection of development-related or aging-related disorders.

Age Estimation

SteppingNet: A Stepping Neural Network with Incremental Accuracy Enhancement

no code implementations27 Nov 2022 Wenhao Sun, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Huaxi Gu, Bing Li, Ulf Schlichtmann

In such platforms, neural networks need to provide acceptable results quickly and the accuracy of the results should be able to be enhanced dynamically according to the computational resources available in the computing system.

Autonomous Vehicles

GANDSE: Generative Adversarial Network based Design Space Exploration for Neural Network Accelerator Design

no code implementations1 Aug 2022 Lang Feng, Wenjian Liu, Chuliang Guo, Ke Tang, Cheng Zhuo, Zhongfeng Wang

To improve the design quality while saving the cost, design automation for neural network accelerators was proposed, where design space exploration algorithms are used to automatically search the optimized accelerator design within a design space.

Generative Adversarial Network

RT-DNAS: Real-time Constrained Differentiable Neural Architecture Search for 3D Cardiac Cine MRI Segmentation

no code implementations8 Jun 2022 Qing Lu, Xiaowei Xu, Shunjie Dong, Cong Hao, Lei Yang, Cheng Zhuo, Yiyu Shi

Accurately segmenting temporal frames of cine magnetic resonance imaging (MRI) is a crucial step in various real-time MRI guided cardiac interventions.

MRI segmentation Neural Architecture Search

OTFPF: Optimal Transport-Based Feature Pyramid Fusion Network for Brain Age Estimation with 3D Overlapped ConvNeXt

2 code implementations10 May 2022 Yu Fu, Yanyan Huang, Yalin Wang, Shunjie Dong, Le Xue, Xunzhao Yin, Qianqian Yang, Yiyu Shi, Cheng Zhuo

In this paper, we propose an end-to-end neural network architecture, referred to as optimal transport based feature pyramid fusion (OTFPF) network, for the brain age estimation with T1 MRIs.

Age Estimation

Worst-Case Dynamic Power Distribution Network Noise Prediction Using Convolutional Neural Network

no code implementations27 Apr 2022 Xiao Dong, Yufei Chen, Xunzhao Yin, Cheng Zhuo

Worst-case dynamic PDN noise analysis is an essential step in PDN sign-off to ensure the performance and reliability of chips.

BIG-bench Machine Learning

Activate index: an integrated index to reveal disrupted brain network organizations of major depressive disorder patients

no code implementations14 Feb 2022 Yu Fu, Yanyan Huang, Meng Niu, Le Xue, Shunjie Dong, Shunlin Guo, Junqiang Lei, Cheng Zhuo

This study for the first time discussed the differences between MDD and HC using both rich club and diverse club metrics and found the complementarity of them in analyzing brain networks.

A resource-efficient deep learning framework for low-dose brain PET image reconstruction and analysis

no code implementations14 Feb 2022 Yu Fu, Shunjie Dong, Yi Liao, Le Xue, Yuanfan Xu, Feng Li, Qianqian Yang, Tianbai Yu, Mei Tian, Cheng Zhuo

18F-fluorodeoxyglucose (18F-FDG) Positron Emission Tomography (PET) imaging usually needs a full-dose radioactive tracer to obtain satisfactory diagnostic results, which raises concerns about the potential health risks of radiation exposure, especially for pediatric patients.

Generative Adversarial Network Image Reconstruction

Lithography Hotspot Detection via Heterogeneous Federated Learning with Local Adaptation

no code implementations9 Jul 2021 Xuezhong Lin, Jingyu Pan, Jinming Xu, Yiran Chen, Cheng Zhuo

Moreover, the design houses are also unwilling to directly share such data with the other houses to build a unified model, which can be ineffective for the design house with unique design patterns due to data insufficiency.

Federated Learning

RCoNet: Deformable Mutual Information Maximization and High-order Uncertainty-aware Learning for Robust COVID-19 Detection

no code implementations22 Feb 2021 Shunjie Dong, Qianqian Yang, Yu Fu, Mei Tian, Cheng Zhuo

The novel 2019 Coronavirus (COVID-19) infection has spread world widely and is currently a major healthcare challenge around the world.

Computed Tomography (CT)

DeU-Net: Deformable U-Net for 3D Cardiac MRI Video Segmentation

no code implementations13 Jul 2020 Shunjie Dong, Jinlong Zhao, Maojun Zhang, Zhengxue Shi, Jianing Deng, Yiyu Shi, Mei Tian, Cheng Zhuo

In this paper, we propose a novel Deformable U-Net (DeU-Net) to fully exploit spatio-temporal information from 3D cardiac MRI video, including a Temporal Deformable Aggregation Module (TDAM) and a Deformable Global Position Attention (DGPA) network.

Video Segmentation Video Semantic Segmentation

MS-NAS: Multi-Scale Neural Architecture Search for Medical Image Segmentation

no code implementations13 Jul 2020 Xingang Yan, Weiwen Jiang, Yiyu Shi, Cheng Zhuo

The recent breakthroughs of Neural Architecture Search (NAS) have motivated various applications in medical image segmentation.

Image Segmentation Medical Image Segmentation +3

Cross-denoising Network against Corrupted Labels in Medical Image Segmentation with Domain Shift

no code implementations19 Jun 2020 Qinming Zhang, Luyan Liu, Kai Ma, Cheng Zhuo, Yefeng Zheng

However, \textit{domain shift} and \textit{corrupted annotations}, which are two common problems in medical imaging, dramatically degrade the performance of DCNNs in practice.

Denoising Image Segmentation +2

Private Knowledge Transfer via Model Distillation with Generative Adversarial Networks

no code implementations5 Apr 2020 Di Gao, Cheng Zhuo

In this paper, we present a novel private knowledge transfer strategy, where the private teacher trained on sensitive data is not publicly accessible but teaches a student to be publicly released.

Privacy Preserving Transfer Learning

When Single Event Upset Meets Deep Neural Networks: Observations, Explorations, and Remedies

1 code implementation10 Sep 2019 Zheyu Yan, Yiyu Shi, Wang Liao, Masanori Hashimoto, Xichuan Zhou, Cheng Zhuo

We are then able to analytically explore the weakness of a network and summarize the key findings for the impact of SIPP on different types of bits in a floating point parameter, layer-wise robustness within the same network and impact of network depth.

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