no code implementations • 25 Jan 2024 • Aniruddha Rajendra Rao, HaiYan Wang, Chetan Gupta
This research addresses a significant gap in port analysis models for vessel Stay and Delay times, offering a valuable contribution to the field of maritime logistics.
no code implementations • 24 Dec 2023 • Wan Wang, HaiYan Wang, Adam J. Sobey
Academic/practical: However, learning in continuously varying environments remains a challenge in the reinforcement learning literature. Methodology: This paper therefore seeks to address whether agents can control varying supply chain problems, transferring learning between environments that require different strategies and avoiding catastrophic forgetting of tasks that have not been seen in a while.
no code implementations • 29 Nov 2023 • HaiYan Wang
We apply QSVMF for feature selection on a breast cancer dataset, comparing the performance of QSVMF against classical approaches with the selected features.
no code implementations • 22 Aug 2023 • HaiYan Wang
Furthermore, we demonstrate that the separability indexes of data can be leveraged to estimate the number of non-local gates required for the quantum support vector machine's feature maps.
no code implementations • 1 Jan 2023 • Aniruddha Rajendra Rao, HaiYan Wang, Chetan Gupta
The rise in data has led to the need for dimension reduction techniques, especially in the area of non-scalar variables, including time series, natural language processing, and computer vision.
no code implementations • 4 Nov 2022 • Zhengyong Huang, Sijuan Zou, Guoshuai Wang, Zixiang Chen, Hao Shen, HaiYan Wang, Na Zhang, Lu Zhang, Fan Yang, Haining Wangg, Dong Liang, Tianye Niu, Xiaohua Zhuc, Zhanli Hua
In this paper, we propose a deep learning segmentation method based on multimodal positron emission tomography-computed tomography (PET-CT), which combines the high sensitivity of PET and the precise anatomical information of CT. We design an improved spatial attention network(ISA-Net) to increase the accuracy of PET or CT in detecting tumors, which uses multi-scale convolution operation to extract feature information and can highlight the tumor region location information and suppress the non-tumor region location information.
no code implementations • 27 Jul 2022 • Takuya Kanazawa, HaiYan Wang, Chetan Gupta
Uncertainty quantification is one of the central challenges for machine learning in real-world applications.
no code implementations • 20 Apr 2022 • HaiYan Wang, YingLi Tian
Point cloud has drawn more and more research attention as well as real-world applications.
no code implementations • 5 Apr 2022 • Ji Fang, Vincent CS Lee, HaiYan Wang
This paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.
no code implementations • 3 Apr 2022 • Ji Fang, Vincent CS Lee, Hao Ji, HaiYan Wang
This study aims to fill this gap by developing a machine learning algorithm that dynamically updates auto-suggestion exercise goals using retrospective data and realistic behavior trajectory.
no code implementations • CVPR 2022 • HaiYan Wang, Will Hutchcroft, Yuguang Li, Zhiqiang Wan, Ivaylo Boyadzhiev, YingLi Tian, Sing Bing Kang
In this paper, we propose a new deep learning-based method for estimating room layout given a pair of 360 panoramas.
1 code implementation • 29 Mar 2022 • Ziyue Feng, Liang Yang, Longlong Jing, HaiYan Wang, YingLi Tian, Bing Li
Conventional self-supervised monocular depth prediction methods are based on a static environment assumption, which leads to accuracy degradation in dynamic scenes due to the mismatch and occlusion problems introduced by object motions.
no code implementations • 18 Jan 2022 • Hamed Khorasgani, HaiYan Wang, Hsiu-Khuern Tang, Chetan Gupta
Traditionally, the performance of multi-agent deep reinforcement learning algorithms are demonstrated and validated in gaming environments where we often have a fixed number of agents.
no code implementations • 28 Sep 2021 • Hamed Khorasgani, HaiYan Wang, Chetan Gupta, Ahmed Farahat
Several machine learning and deep learning frameworks have been proposed to solve remaining useful life estimation and failure prediction problems in recent years.
no code implementations • 28 Sep 2021 • Hamed Khorasgani, HaiYan Wang, Chetan Gupta, Susumu Serita
Our method can learn complex policies to achieve long-term goals and at the same time it can be easily adjusted to address short-term requirements without retraining.
1 code implementation • CVPR 2021 • HaiYan Wang, Jiahao Pang, Muhammad A. Lodhi, YingLi Tian, Dong Tian
Scene flow depicts the dynamics of a 3D scene, which is critical for various applications such as autonomous driving, robot navigation, AR/VR, etc.
no code implementations • 28 Dec 2020 • Luann C. Jung, HaiYan Wang
For humans learning to categorize and distinguish parts of the world, the set of assumptions (overhypotheses) they hold about potential category structures is directly related to their learning process.
Computational Engineering, Finance, and Science
no code implementations • 24 Nov 2020 • Qiyao Wang, HaiYan Wang, Chetan Gupta, Aniruddha Rajendra Rao, Hamed Khorasgani
Specifically, we aim to learn mathematical mappings from multiple chronologically measured numerical variables within a certain time interval S to multiple numerical variables of interest over time interval T. Prior arts, including the multivariate regression model, the Seq2Seq model, and the functional linear models, suffer from several limitations.
no code implementations • 9 Nov 2020 • Hamed Khorasgani, HaiYan Wang, Chetan Gupta
In this paper, we review the main challenges in using deep RL to address the dynamic dispatching problem in the mining industry.
no code implementations • 4 Sep 2020 • Nao Yamamoto, HaiYan Wang
In June 2020, Arizona, U. S., emerged as one of the world's worst coronavirus disease 2019(COVID-19) spots after the stay-at-home order was lifted in the middle of May.
Populations and Evolution Physics and Society
no code implementations • 20 Aug 2020 • Jinglun Feng, Liang Yang, HaiYan Wang, Yifeng Song, Jizhong Xiao
This system is composed of three modules: 1) visual inertial fusion (VIF) module to generate the pose information of GPR device, 2) deep neural network module (i. e., DepthNet) which detects B-scan of GPR image, extracts hyperbola features to remove the noise in B-scan data and predicts dielectric to determine the depth of the objects, 3) 3D GPR migration module which synchronizes the pose information with GPR scan data processed by DepthNet to reconstruct and visualize the 3D underground targets.
no code implementations • 8 Jan 2020 • Yufang Wang, HaiYan Wang
The paper is the first attempt to apply a PDE model to the bitcoin transaction network for predicting bitcoin price.
no code implementations • 11 Dec 2017 • Zexun Zhou, Zhongshi He, Ziyu Chen, Yuanyuan Jia, HaiYan Wang, Jinglong Du, Dingding Chen
The proposed network is consist of multiple context modeling and prediction modules, which are in order to detect small, blur, occluded and diverse pose faces.