Search Results for author: Yuhan Dong

Found 17 papers, 3 papers with code

Bayesian Beamforming for Integrated Sensing and Communication Systems

no code implementations10 Feb 2025 Zongyao Zhao, Zhenyu Liu, Wei Dai, Xinke Tang, Xiao-Ping Zhang, Yuhan Dong

The uncertainty of the sensing target brings great challenge to the beamforming design of the integrated sensing and communication (ISAC) system.

Integrated sensing and communication ISAC

Misaligned Over-The-Air Computation of Multi-Sensor Data with Wiener-Denoiser Network

1 code implementation1 Sep 2024 Mingjun Du, Sihui Zheng, Xiao-Ping Zhang, Yuhan Dong

In data driven deep learning, distributed sensing and joint computing bring heavy load for computing and communication.

Denoising Image Deblurring

B-ISAC: Backscatter Integrated Sensing and Communication for IoE Applications

no code implementations27 Jul 2024 Zongyao Zhao, Yuhan Dong, Tiankuo Wei, Xinke Tang, Xiao-Ping Zhang, Zhenyu Liu

In this paper, we propose a novel cognitive wireless system called backscatter-ISAC (B-ISAC) and develop a joint beamforming framework for different stages (task modes).

Integrated sensing and communication ISAC +1

FlashDecoding++: Faster Large Language Model Inference on GPUs

no code implementations2 Nov 2023 Ke Hong, Guohao Dai, Jiaming Xu, Qiuli Mao, Xiuhong Li, Jun Liu, Kangdi Chen, Yuhan Dong, Yu Wang

A single and static dataflow may lead to a 50. 25% performance loss for GEMMs of different shapes in LLM inference.

Language Modeling Language Modelling +2

Contrastive Learning for Low-light Raw Denoising

no code implementations5 May 2023 Taoyong Cui, Yuhan Dong

Inspired by the success of contrastive learning used in some high-level computer vision tasks, we bring in this idea to the low-level denoising task.

Contrastive Learning Denoising +1

Bokeh Rendering Based on Adaptive Depth Calibration Network

no code implementations21 Feb 2023 Lu Liu, Lei Zhou, Yuhan Dong

This allows the camera to capture images with shallow depth-of-field, in which only a small area of the image is in sharp focus, while the rest of the image is blurred.

Monocular Depth Estimation

Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading

no code implementations13 Feb 2023 Fei Kong, Xiyue Wang, Jinxi Xiang, Sen yang, Xinran Wang, Meng Yue, Jun Zhang, Junhan Zhao, Xiao Han, Yuhan Dong, Biyue Zhu, Fang Wang, Yueping Liu

We assessed the effectiveness of FACL in cancer diagnosis and Gleason grading tasks using 19, 461 whole-slide images of prostate cancer from multiple centers.

Contrastive Learning Ethics +2

TAOTF: A Two-stage Approximately Orthogonal Training Framework in Deep Neural Networks

no code implementations25 Nov 2022 Taoyong Cui, Jianze Li, Yuhan Dong, Li Liu

In the first stage, we propose a novel algorithm called polar decomposition-based orthogonal initialization (PDOI) to find a good initialization for the orthogonal optimization.

CLOSE: Curriculum Learning On the Sharing Extent Towards Better One-shot NAS

1 code implementation16 Jul 2022 Zixuan Zhou, Xuefei Ning, Yi Cai, Jiashu Han, Yiping Deng, Yuhan Dong, Huazhong Yang, Yu Wang

Specifically, we train the supernet with a large sharing extent (an easier curriculum) at the beginning and gradually decrease the sharing extent of the supernet (a harder curriculum).

Neural Architecture Search

A Fair Federated Learning Framework With Reinforcement Learning

no code implementations26 May 2022 Yaqi Sun, Shijing Si, Jianzong Wang, Yuhan Dong, Zhitao Zhu, Jing Xiao

More importantly, we apply the Gini coefficient and validation accuracy of clients in each communication round to construct a reward function for the reinforcement learning.

Fairness Federated Learning +3

RCMNet: A deep learning model assists CAR-T therapy for leukemia

no code implementations6 May 2022 Ruitao Zhang, Xueying Han, Ijaz Gul, Shiyao Zhai, Ying Liu, Yongbing Zhang, Yuhan Dong, Lan Ma, Dongmei Yu, Jin Zhou, Peiwu Qin

Although testing on the CAR-T cells dataset, a decent performance is observed, which is attributed to the limited size of the dataset.

Diagnostic Image Classification +1

Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference

no code implementations6 May 2022 Yang Liu, Ersi Zhang, Lulu Xu, Chufan Xiao, Xiaoyun Zhong, Lijin Lian, Fang Li, Bin Jiang, Yuhan Dong, Lan Ma, Qiming Huang, Ming Xu, Yongbing Zhang, Dongmei Yu, Chenggang Yan, Peiwu Qin

Deep learning techniques have shown great potential in medical image processing, particularly through accurate and reliable image segmentation on magnetic resonance imaging (MRI) scans or computed tomography (CT) scans, which allow the localization and diagnosis of lesions.

Computed Tomography (CT) Image Segmentation +3

Point Cloud Color Constancy

1 code implementation CVPR 2022 Xiaoyan Xing, Yanlin Qian, Sibo Feng, Yuhan Dong, Jiri Matas

In this paper, we present Point Cloud Color Constancy, in short PCCC, an illumination chromaticity estimation algorithm exploiting a point cloud.

Color Constancy

Driving maneuvers prediction based on cognition-driven and data-driven method

no code implementations8 May 2018 Dong Zhou, Huimin Ma, Yuhan Dong

To overcome this challenge, we propose a novel method that combines both the cognition-driven model and the data-driven model.

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