Search Results for author: Juan Zou

Found 15 papers, 1 papers with code

An Evolutionary Network Architecture Search Framework with Adaptive Multimodal Fusion for Hand Gesture Recognition

no code implementations27 Mar 2024 Yizhang Xia, Shihao Song, Zhanglu Hou, Junwen Xu, Juan Zou, YuAn Liu, Shengxiang Yang

To automatically adapt to various datasets, the ENAS framework is designed to automatically search a MHGR network with appropriate fusion positions and ratios.

Hand Gesture Recognition Hand-Gesture Recognition

Multiple Population Alternate Evolution Neural Architecture Search

no code implementations11 Mar 2024 Juan Zou, Han Chu, Yizhang Xia, Junwen Xu, YuAn Liu, Zhanglu Hou

Specifically, the global search space requires a significant amount of computational resources and time, the scalable search space sacrifices the diversity of network structures and the hierarchical search space increases the search cost in exchange for network diversity.

Neural Architecture Search

G-EvoNAS: Evolutionary Neural Architecture Search Based on Network Growth

no code implementations5 Mar 2024 Juan Zou, Weiwei Jiang, Yizhang Xia, YuAn Liu, Zhanglu Hou

The process begins from a shallow network, grows and evolves, and gradually deepens into a complete network, reducing the search complexity in the global space.

Image Classification Neural Architecture Search

Simultaneous q-Space Sampling Optimization and Reconstruction for Fast and High-fidelity Diffusion Magnetic Resonance Imaging

no code implementations3 Jan 2024 Jing Yang, Jian Cheng, Cheng Li, Wenxin Fan, Juan Zou, Ruoyou Wu, Shanshan Wang

Diffusion Magnetic Resonance Imaging (dMRI) plays a crucial role in the noninvasive investigation of tissue microstructural properties and structural connectivity in the \textit{in vivo} human brain.

Combining Kernelized Autoencoding and Centroid Prediction for Dynamic Multi-objective Optimization

no code implementations2 Dec 2023 Zhanglu Hou, Juan Zou, Gan Ruan, YuAn Liu, Yizhang Xia

Evolutionary algorithms face significant challenges when dealing with dynamic multi-objective optimization because Pareto optimal solutions and/or Pareto optimal fronts change.

Evolutionary Algorithms

TS-ENAS:Two-Stage Evolution for Cell-based Network Architecture Search

no code implementations14 Oct 2023 Juan Zou, Shenghong Wu, Yizhang Xia, Weiwei Jiang, Zeping Wu, Jinhua Zheng

In our algorithm, a new cell-based search space and an effective two-stage encoding method are designed to represent cells and neural network structures.

Image Classification

Generalizable Learning Reconstruction for Accelerating MR Imaging via Federated Neural Architecture Search

no code implementations27 Aug 2023 Ruoyou Wu, Cheng Li, Juan Zou, Shanshan Wang

Heterogeneous data captured by different scanning devices and imaging protocols can affect the generalization performance of the deep learning magnetic resonance (MR) reconstruction model.

Efficient Neural Network Fairness +4

FedAutoMRI: Federated Neural Architecture Search for MR Image Reconstruction

no code implementations21 Jul 2023 Ruoyou Wu, Cheng Li, Juan Zou, Shanshan Wang

Centralized training methods have shown promising results in MR image reconstruction, but privacy concerns arise when gathering data from multiple institutions.

Federated Learning Image Reconstruction +1

Self-Supervised Federated Learning for Fast MR Imaging

no code implementations10 May 2023 Juan Zou, Cheng Li, Ruoyou Wu, Tingrui Pei, Hairong Zheng, Shanshan Wang

SSFedMRI explores the physics-based contrastive reconstruction networks in each client to realize cross-site collaborative training in the absence of fully sampled data.

Federated Learning Image Reconstruction

Model-based Federated Learning for Accurate MR Image Reconstruction from Undersampled k-space Data

no code implementations15 Apr 2023 Ruoyou Wu, Cheng Li, Juan Zou, Qiegen Liu, Hairong Zheng, Shanshan Wang

However, high heterogeneity exists in the data from different centers, and existing federated learning methods tend to use average aggregation methods to combine the client's information, which limits the performance and generalization capability of the trained models.

Federated Learning Image Reconstruction

Iterative Data Refinement for Self-Supervised MR Image Reconstruction

no code implementations24 Nov 2022 Xue Liu, Juan Zou, Xiawu Zheng, Cheng Li, Hairong Zheng, Shanshan Wang

Then, we design an effective self-supervised training data refinement method to reduce this data bias.

Image Reconstruction

SelfCoLearn: Self-supervised collaborative learning for accelerating dynamic MR imaging

no code implementations8 Aug 2022 Juan Zou, Cheng Li, Sen Jia, Ruoyou Wu, Tingrui Pei, Hairong Zheng, Shanshan Wang

Lately, deep learning has been extensively investigated for accelerating dynamic magnetic resonance (MR) imaging, with encouraging progresses achieved.

Data Augmentation Image Reconstruction

Dynamical instabilities for model with point-coupling interactions: Vlasov formalism method

no code implementations14 Dec 2020 Yanjun Chen, Juan Zou, Zipeng Cheng, Binguang He

We explore the effects of the density dependence of symmetry energy on the dynamical instabilities and crust-core phase transition in the cold and warm neutron stars in the RMF theory with point-coupling interactions using the Vlasov approach.

Nuclear Theory

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