Search Results for author: Qianqian Yang

Found 14 papers, 2 papers with code

Semantic-preserved Communication System for Highly Efficient Speech Transmission

no code implementations25 May 2022 Tianxiao Han, Qianqian Yang, Zhiguo Shi, Shibo He, Zhaoyang Zhang

Deep learning (DL) based semantic communication methods have been explored for the efficient transmission of images, text, and speech in recent years.

Speech Recognition

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

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.

Image Reconstruction

Wireless Transmission of Images With The Assistance of Multi-level Semantic Information

no code implementations8 Feb 2022 Zhenguo Zhang, Qianqian Yang, Shibo He, Mingyang Sun, Jiming Chen

In particular, the proposed model includes a multilevel semantic feature extractor, that extracts both the highlevel semantic information, such as the text semantics and the segmentation semantics, and the low-level semantic information, such as local spatial details of the images.

Semantic Segmentation

Semantic-aware Speech to Text Transmission with Redundancy Removal

no code implementations7 Feb 2022 Tianxiao Han, Qianqian Yang, Zhiguo Shi, Shibo He, Zhaoyang Zhang

We also propose a two-stage training scheme, which speeds up the training of the proposed DL model.

Blind Channel Estimation for MIMO Systems via Variational Inference

no code implementations16 Nov 2021 Jiancheng Tang, Qianqian Yang, Zhaoyang Zhang

In this paper, we investigate the blind channel estimation problem for MIMO systems under Rayleigh fading channel.

Variational Inference

JMSNAS: Joint Model Split and Neural Architecture Search for Learning over Mobile Edge Networks

no code implementations16 Nov 2021 Yuqing Tian, Zhaoyang Zhang, Zhaohui Yang, Qianqian Yang

In this paper, a joint model split and neural architecture search (JMSNAS) framework is proposed to automatically generate and deploy a DNN model over a mobile edge network.

Neural Architecture Search

FTPipeHD: A Fault-Tolerant Pipeline-Parallel Distributed Training Framework for Heterogeneous Edge Devices

no code implementations6 Oct 2021 Yuhao Chen, Qianqian Yang, Shibo He, Zhiguo Shi, Jiming Chen

Our numerical results demonstrate that FTPipeHD is 6. 8x faster in training than the state of the art method when the computing capacity of the best device is 10x greater than the worst one.

Communication-Efficient Federated Learning with Binary Neural Networks

1 code implementation5 Oct 2021 Yuzhi Yang, Zhaoyang Zhang, Qianqian Yang

{ Numerical results show that the proposed FL framework significantly reduces the communication cost compared to the conventional neural networks with typical real-valued parameters, and the performance loss incurred by the binarization can be further compensated by a hybrid method.

Binarization 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)

Distributed Deep Convolutional Compression for Massive MIMO CSI Feedback

no code implementations7 Mar 2020 Mahdi Boloursaz Mashhadi, Qianqian Yang, Deniz Gunduz

We also propose a distributed version of DeepCMC for a multi-user MIMO scenario to encode and reconstruct the CSI from multiple users in a distributed manner.

Quantization

CNN-based Analog CSI Feedback in FDD MIMO-OFDM Systems

no code implementations23 Oct 2019 Mahdi Boloursaz Mashhadi, Qianqian Yang, Deniz Gunduz

Massive multiple-input multiple-output (MIMO) systems require downlink channel state information (CSI) at the base station (BS) to better utilize the available spatial diversity and multiplexing gains.

Quantization

Deep Convolutional Compression for Massive MIMO CSI Feedback

no code implementations2 Jul 2019 Qianqian Yang, Mahdi Boloursaz Mashhadi, Deniz Gündüz

In comparison with previous works, the main contributions of DeepCMC are two-fold: i) DeepCMC is fully convolutional, and it can be used in a wide range of scenarios with various numbers of sub-channels and transmit antennas; ii) DeepCMC includes quantization and entropy coding blocks and minimizes a cost function that accounts for both the rate of compression and the reconstruction quality of the channel matrix at the BS.

Quantization

The Multi-layer Information Bottleneck Problem

no code implementations14 Nov 2017 Qianqian Yang, Pablo Piantanida, Deniz Gündüz

Based on information forwarded by the preceding layer, each stage of the network is required to preserve a certain level of relevance with regards to a specific hidden variable, quantified by the mutual information.

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