no code implementations • 26 Mar 2024 • Yongrui Yu, HanYu Chen, Zitian Zhang, Qiong Xiao, Wenhui Lei, Linrui Dai, Yu Fu, Hui Tan, Guan Wang, Peng Gao, Xiaofan Zhang
To address these problems, we present a pipeline that integrates the conditional diffusion model for lymph node generation and the nnU-Net model for lymph node segmentation to improve the segmentation performance of abdominal lymph nodes through synthesizing a diversity of realistic abdominal lymph node data.
no code implementations • 17 Mar 2024 • Jingcheng Jiang, Haiyin Piao, Yu Fu, Yihang Hao, Chuanlu Jiang, Ziqi Wei, Xin Yang
Furthermore, we construct a dogfight scenario for aerial agents to demonstrate the practicality of the PDO algorithm.
no code implementations • 23 Jan 2024 • Chuanbo Liu, Yu Fu, Lu Lin, Elliot L. Elson, Jin Wang
This approach, when combined with the analytical capabilities of a sophisticated deep neural network, enables the accurate estimation of rate constants from observational data in a broad range of biochemical reaction networks.
no code implementations • 20 Jan 2024 • Xi Chen, MingKe You, Li Wang, Weizhi Liu, Yu Fu, Jie Xu, Shaoting Zhang, Gang Chen, Kang Li, Jian Li
This study focused on evaluating and enhancing the clinical capabilities of LLMs in specific domains, using osteoarthritis (OA) management as a case study.
no code implementations • 12 Dec 2023 • Yu Fu, Yufei Li, Wen Xiao, Cong Liu, Yue Dong
Recent developments in balancing the usefulness and safety of Large Language Models (LLMs) have raised a critical question: Are mainstream NLP tasks adequately aligned with safety consideration?
no code implementations • 16 Oct 2023 • Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, Pedram Zaree, Yue Dong, Nael Abu-Ghazaleh
Large Language Models (LLMs) are swiftly advancing in architecture and capability, and as they integrate more deeply into complex systems, the urgency to scrutinize their security properties grows.
1 code implementation • ICCV 2023 • Yanyan Huang, Weiqin Zhao, Shujun Wang, Yu Fu, Yuming Jiang, Lequan Yu
In this paper, we propose the FIRST continual learning framework for WSI analysis, named ConSlide, to tackle the challenges of enormous image size, utilization of hierarchical structure, and catastrophic forgetting by progressive model updating on multiple sequential datasets.
1 code implementation • 25 Jul 2023 • Yu Fu, Deyi Xiong, Yue Dong
To mitigate potential risks associated with language models, recent AI detection research proposes incorporating watermarks into machine-generated text through random vocabulary restrictions and utilizing this information for detection.
no code implementations • 27 Jun 2023 • Haitao Tang, Yu Fu, Lei Sun, Jiabin Xue, Dan Liu, Yongchao Li, Zhiqiang Ma, Minghui Wu, Jia Pan, Genshun Wan, Ming'en Zhao
In this paper, we propose an adaptive two-stage knowledge distillation method consisting of hidden layer learning and output layer learning.
no code implementations • 30 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.
no code implementations • ICCV 2023 • Yu Qiao, Bo Dong, Ao Jin, Yu Fu, Seung-Hwan Baek, Felix Heide, Pieter Peers, Xiaopeng Wei, Xin Yang
In this paper, we present the first polarization-guided video glass segmentation propagation solution (PGVS-Net) that can robustly and coherently propagate glass segmentation in RGB-P video sequences.
no code implementations • 19 Dec 2022 • Yu Fu, Deyi Xiong, Yue Dong
We introduce inverse reinforcement learning (IRL) as an effective paradigm for training abstractive summarization models, imitating human summarization behaviors.
no code implementations • 7 Dec 2022 • Yinpeng Dong, Peng Chen, Senyou Deng, Lianji L, Yi Sun, Hanyu Zhao, Jiaxing Li, Yunteng Tan, Xinyu Liu, Yangyi Dong, Enhui Xu, Jincai Xu, Shu Xu, Xuelin Fu, Changfeng Sun, Haoliang Han, Xuchong Zhang, Shen Chen, Zhimin Sun, Junyi Cao, Taiping Yao, Shouhong Ding, Yu Wu, Jian Lin, Tianpeng Wu, Ye Wang, Yu Fu, Lin Feng, Kangkang Gao, Zeyu Liu, Yuanzhe Pang, Chengqi Duan, Huipeng Zhou, Yajie Wang, Yuhang Zhao, Shangbo Wu, Haoran Lyu, Zhiyu Lin, YiFei Gao, Shuang Li, Haonan Wang, Jitao Sang, Chen Ma, Junhao Zheng, Yijia Li, Chao Shen, Chenhao Lin, Zhichao Cui, Guoshuai Liu, Huafeng Shi, Kun Hu, Mengxin Zhang
The security of artificial intelligence (AI) is an important research area towards safe, reliable, and trustworthy AI systems.
no code implementations • 1 Nov 2022 • Yanyan Huang, Yong Wang, Kun Shi, Chaojie Gu, Yu Fu, Cheng Zhuo, Zhiguo Shi
Gait recognition is widely used in diversified practical applications.
no code implementations • COLING 2022 • Xuming Hu, Zhijiang Guo, Yu Fu, Lijie Wen, Philip S. Yu
A scene graph is a semantic representation that expresses the objects, attributes, and relationships between objects in a scene.
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 • 8 May 2022 • Xueyuan Duan, Yu Fu, Kun Wang
To address the problem that traditional network traffic anomaly detection algorithms do not suffi-ciently mine potential features in long time domain, an anomaly detection method based on mul-ti-scale residual features of network traffic is proposed.
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 • 14 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.
no code implementations • CVPR 2022 • Yixuan Huang, Xiaoyun Zhang, Yu Fu, Siheng Chen, Ya zhang, Yan-Feng Wang, Dazhi He
Those methods conduct the super-resolution task of the input low-resolution(LR) image and the texture transfer task from the reference image together in one module, easily introducing the interference between LR and reference features.
no code implementations • 29 Jul 2021 • Yu Fu, Tianyang Xu, XiaoJun Wu, Josef Kittler
In this paper, we propose a Patch Pyramid Transformer(PPT) to effectively address the above issues. Specifically, we first design a Patch Transformer to transform the image into a sequence of patches, where transformer encoding is performed for each patch to extract local representations.
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 • 21 Feb 2021 • Yu Fu, Xiao-Jun Wu, Josef Kittler
In this paper, we apply the image decomposition network to the image fusion task.
2 code implementations • 24 Jan 2021 • Yu Fu, Xiao-Jun Wu
Deep learning is a rapidly developing approach in the field of infrared and visible image fusion.
Generative Adversarial Network Infrared And Visible Image Fusion +1
no code implementations • 28 Jul 2020 • Yu Fu, Mohammad Dehghani Soltani, Hamada Alshaer, Cheng-Xiang Wang, Majid Safari, Stephen McLaughlin, Harald Haas
This paper proposes an end-to-end (e2e) power consumption model and studies the energy efficiency for a heterogeneous B5G cellular architecture that separates the indoor and outdoor communication scenarios in ultra dense networks.
no code implementations • 28 Jul 2020 • Yu Fu, Cheng-Xiang Wang, Xuming Fang, Li Yan, Stephen McLaughlin
When compared with the V-BLAST system and the channel inversion system, SM approaches offer advantages in performance for MU massive MIMO systems.
1 code implementation • 27 Jul 2020 • Yu Fu, Alexander W Jung, Ramon Viñas Torne, Santiago Gonzalez, Harald Vöhringer, Artem Shmatko, Lucy Yates, Mercedes Jimenez-Linan, Luiza Moore, Moritz Gerstung
These findings demonstrate the large potential of computer vision to characterise the molecular basis of tumour histopathology and lay out a rationale for integrating molecular and histopathological data to augment diagnostic and prognostic workflows.
no code implementations • 23 Dec 2019 • Yu Fu, Cheng-Xiang Wang, Zijun Zhao, Stephen McLaughlin
In this paper, we consider a heterogeneous 5G cellular architecture that separates the outdoor and indoor scenarios and in particular study the trade-off between the spectrum efficiency (SE), energy efficiency (EE), economy efficiency (ECE).
no code implementations • 7 Feb 2019 • Liang Cheng, Yang Zhang, Yi Zhang, Chen Wu, Zhangtan Li, Yu Fu, Haisheng Li
Our experiments on a set of widely used PDF viewers demonstrate that the improved seed inputs produced by our framework could significantly increase the code coverage of the target program and the likelihood of detecting program crashes.
Cryptography and Security