no code implementations • 29 Apr 2024 • Yuxuan Yan, Shunpu Tang, Zhiguo Shi, Qianqian Yang
However, we observe that the non-IID data in federated learning leads to a gap in performance between the PEFT method and full parameter fine-tuning(FFT).
no code implementations • 18 Apr 2024 • Shunpu Tang, Chen Liu, Qianqian Yang, Shibo He, Dusit Niyato
To address this issue, we propose a novel secure semantic communication (SemCom) approach for image transmission, which integrates steganography technology to conceal private information within non-private images (host images).
1 code implementation • 29 Mar 2024 • Shunpu Tang, Qianqian Yang, Deniz Gündüz, Zhaoyang Zhang
In this paper, we explore an evolving semantic communication system for image transmission, referred to as ESemCom, with the capability to continuously enhance transmission efficiency.
no code implementations • 1 Jan 2024 • Yulin Shao, Chenghong Bian, Li Yang, Qianqian Yang, Zhaoyang Zhang, Deniz Gunduz
Acquisition and processing of point clouds (PCs) is a crucial enabler for many emerging applications reliant on 3D spatial data, such as robot navigation, autonomous vehicles, and augmented reality.
no code implementations • 8 Dec 2023 • Zhenguo Zhang, Qianqian Yang, Shibo He, Jiming Chen
Semantic communication has emerged as a promising approach for improving efficient transmission in the next generation of wireless networks.
no code implementations • 22 Nov 2023 • Yuhao Chen, Yuxuan Yan, Qianqian Yang, Yuanchao Shu, Shibo He, Jiming Chen
Transformer-based large language models (LLMs) have demonstrated impressive capabilities in a variety of natural language processing (NLP) tasks.
no code implementations • 10 Nov 2023 • Yuhao Chen, Yuxuan Yan, Qianqian Yang, Yuanchao Shu, Shibo He, Zhiguo Shi, Jiming Chen
Moreover, we propose a bit-level computation-efficient data compression scheme to compress the data to be transmitted between devices during training.
no code implementations • 8 Aug 2023 • Yuhao Chen, Qianqian Yang, Zhiguo Shi, Jiming Chen
In recent years, semantic communication has been a popular research topic for its superiority in communication efficiency.
no code implementations • 23 Jun 2023 • Tianxiao Han, Kaiyi Chi, Qianqian Yang, Zhiguo Shi
As three-dimensional (3D) data acquisition devices become increasingly prevalent, the demand for 3D point cloud transmission is growing.
no code implementations • 5 Jun 2023 • Weixuan Chen, Yuhao Chen, Qianqian Yang, Chongwen Huang, Qian Wang, Zhaoyang Zhang
Adaptive rate control for deep joint source and channel coding (JSCC) is considered as an effective approach to transmit sufficient information in scenarios with limited communication resources.
no code implementations • 4 Jun 2023 • Kaiyi Chi, Yingzhi Huang, Qianqian Yang, Zhaohui Yang, Zhaoyang Zhang
Precoding design for the downlink of multiuser multiple-input multiple-output (MU-MIMO) systems is a fundamental problem.
no code implementations • 12 May 2023 • Senthil Kumar Jagatheesaperumal, Zhaohui Yang, Qianqian Yang, Chongwen Huang, Wei Xu, Mohammad Shikh-Bahaei, Zhaoyang Zhang
To facilitate the deployment of digital twins in Metaverse, the paradigm with semantic awareness has been proposed as a means for enabling accurate and task-oriented information extraction with inherent intelligence.
no code implementations • 30 Nov 2022 • Megan E. Farquhar, Qianqian Yang, Viktor Vegh
In summary, our findings suggest robust, fast and accurate estimation of mean kurtosis can be realised within a clinically feasible diffusion weighted magnetic resonance imaging data acquisition time.
no code implementations • 18 Nov 2022 • Tianxiao Han, Jiancheng Tang, Qianqian Yang, Yiping Duan, Zhaoyang Zhang, Zhiguo Shi
Deep learning (DL) based semantic communication methods have been explored to transmit images efficiently in recent years.
1 code implementation • 27 May 2022 • Qiyuan Wang, Qianqian Yang, Shibo He, Zhiguo Shi, Jiming Chen
In an asynchronous federated learning framework, the server updates the global model once it receives an update from a client instead of waiting for all the updates to arrive as in the synchronous setting.
no code implementations • 25 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.
2 code implementations • 10 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.
no code implementations • 14 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.
no code implementations • 8 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.
no code implementations • 7 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.
no code implementations • 16 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.
no code implementations • 16 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.
no code implementations • 6 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.
1 code implementation • 5 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.
no code implementations • 22 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.
no code implementations • 7 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.
no code implementations • 23 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.
no code implementations • 2 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.
no code implementations • 14 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.