no code implementations • 24 Feb 2024 • Sipei Zhao, Fei Ma
Acoustic beamforming aims to focus acoustic signals to a specific direction and suppress undesirable interferences from other directions.
no code implementations • 14 Feb 2024 • Fei Ma, Sipei Zhao, Ian S. Burnett
Sound field reconstruction (SFR) augments the information of a sound field captured by a microphone array.
no code implementations • 9 Feb 2024 • Zixun Lan, Binjie Hong, Jiajun Zhu, Zuo Zeng, Zhenfu Liu, Limin Yu, Fei Ma
As a semi-template-based method RetroSiG has several advantages.
no code implementations • 4 Dec 2023 • Haoqi Yan, Haoyuan Xu, Hongbo Gao, Fei Ma, Shengbo Eben Li, Jingliang Duan
To tackle these challenges, this study proposes an integrated drill boom control method based on Reinforcement Learning (RL).
no code implementations • 15 Oct 2023 • Wangyu Wu, Tianhong Dai, Xiaowei Huang, Fei Ma, Jimin Xiao
In this paper, we introduce a novel ViT-based WSSS method named top-K pooling with patch contrastive learning (TKP-PCL), which employs a top-K pooling layer to alleviate the limitations of previous max pooling selection.
Contrastive Learning Weakly supervised Semantic Segmentation +1
no code implementations • 15 Oct 2023 • Wangyu Wu, Tianhong Dai, Xiaowei Huang, Fei Ma, Jimin Xiao
In this process, the existing images and image-level labels provide the necessary control information, where GPT is employed to enrich the prompts, leading to the generation of diverse backgrounds.
1 code implementation • 19 Sep 2023 • Yile, Zhang, Fei Ma, Thushara Abhayapala, Prasanga Samarasinghe, Amy Bastine
An ANC system is designed to take advantage of the interpolated signal to reduce noise signal within the ROI.
1 code implementation • 15 Sep 2023 • Xingyu Chen, Fei Ma, Yile Zhang, Amy Bastine, Prasanga N. Samarasinghe
The proposed method realizes the convolution process by decomposing and reconstructing HRTF through the Spherical Harmonics (SHs).
no code implementations • 12 Sep 2023 • Jiajun Zhu, Zichuan Yang, Binjie Hong, Jiacheng Song, Jiwei Wang, Tianhao Chen, Shuilan Yang, Zixun Lan, Fei Ma
Correcting students' multiple-choice answers is a repetitive and mechanical task that can be considered an image multi-classification task.
no code implementations • 1 Aug 2023 • Fei Ma, Thushara D. Abhayapala, Prasanga N. Samarasinghe
A PINN models the measurement of an OSMA and predicts the sound field on another sphere whose radius is different from that of the OSMA.
1 code implementation • 27 Jul 2023 • Fei Ma, Thushara D. Abhayapala, Prasanga N. Samarasinghe, Xingyu Chen
Head-related transfer function (HRTF) capture the information that a person uses to localize sound sources in space, and thus is crucial for creating personalized virtual acoustic experiences.
1 code implementation • 26 Jul 2023 • Xingyu Chen, Fei Ma, Amy Bastine, Prasanga Samarasinghe, Huiyuan Sun
To overcome this challenge, this paper proposes a method for sound field estimation based on a physics-informed neural network.
1 code implementation • 18 Jul 2023 • Lulu Liu, Runwei Guan, Fei Ma, Jeremy Smith, Yutao Yue
Therefore, interference mitigation is of great significance for millimeter-wave radar-based target detection.
no code implementations • 28 Jan 2023 • Zixun Lan, Zuo Zeng, Binjie Hong, Zhenfu Liu, Fei Ma
The critical insight in this framework is that the single or multiple reaction center must be a node-induced subgraph of the molecular product graph.
no code implementations • 25 Oct 2022 • Fei Ma, Feiyi Liu, Wei Li
In this paper, we introduce an approach of GNNs combined with a HaarPooling operation to analyze the events, called HaarPooling Message Passing neural network (HMPNet).
no code implementations • 9 Aug 2022 • Zixun Lan, Binjie Hong, Ye Ma, Fei Ma
Our critical insight into INFMCS is the strong correlation between similarity score and Maximum Common Subgraph (MCS).
no code implementations • 2 Apr 2022 • Daochang Wang, Fan Zhang, Fei Ma, Wei Hu, Yu Tang, Yongsheng Zhou
As a result, deep learning methods have not been fully used in airport detection tasks.
no code implementations • 2 Mar 2022 • Xianbin Ye, Ziliang Li, Fei Ma, Zongbi Yi, Pengyong Li, Jun Wang, Peng Gao, Yixuan Qiao, Guotong Xie
Anti-cancer drug discoveries have been serendipitous, we sought to present the Open Molecular Graph Learning Benchmark, named CandidateDrug4Cancer, a challenging and realistic benchmark dataset to facilitate scalable, robust, and reproducible graph machine learning research for anti-cancer drug discovery.
no code implementations • 26 Oct 2021 • Pengyong Li, Jun Wang, Ziliang Li, Yixuan Qiao, Xianggen Liu, Fei Ma, Peng Gao, Seng Song, Guotong Xie
Self-supervised learning has gradually emerged as a powerful technique for graph representation learning.
no code implementations • 24 Aug 2021 • Fei Ma, Xiangxiang Xu, Shao-Lun Huang, Lin Zhang
Moreover, we develop a generalized form of the softmax function to effectively implement maximum likelihood estimation in an end-to-end manner.
no code implementations • 18 May 2021 • Fei Ma, Thushara D. Abhayapala, Prasanga N. Samarasinghe
The time-domain implementation makes the beamformer output suitable for further use by real-time applications, the nearfield focusing enables the beamforming method to suppress an interference even if it is in the same direction as the target source, and the frequency-invariant beampattern makes the beamforming method suitable for enhancing the target source over a broad frequency band.
no code implementations • 1 Apr 2021 • Zixun Lan, Limin Yu, Linglong Yuan, Zili Wu, Qiang Niu, Fei Ma
Comparing with the previous GNNs-based methods for subgraph matching task, our proposed Sub-GMN allows varying query and data graphes in the test/application stage, while most previous GNNs-based methods can only find a matched subgraph in the data graph during the test/application for the same query graph used in the training stage.
no code implementations • 4 Mar 2021 • Sifan Song, Daiyun Huang, Yalun Hu, Chunxiao Yang, Jia Meng, Fei Ma, Frans Coenen, Jiaming Zhang, Jionglong Su
To address the flaws in the geometric algorithms, we propose a novel framework based on image-to-image translation to learn a pertinent mapping dependence for synthesizing straightened chromosomes with uninterrupted banding patterns and preserved details.
no code implementations • 30 May 2020 • Fan Zhang, MinChao Yan, Chen Hu, Jun Ni, Fei Ma
In addition, a dual-branch convolutional neural network (CNN) classification method is designed in combination with the global information to mine the pixel features of the image.
no code implementations • 11 Sep 2019 • Jingliang Duan, Jie Li, Qiang Ge, Shengbo Eben Li, Monimoy Bujarbaruah, Fei Ma, Dezhao Zhang
The warm-up phase minimizes the square of the Hamiltonian to achieve admissibility, while the generalized policy iteration phase relaxes the update termination conditions for faster convergence.