Search Results for author: Ye Li

Found 31 papers, 9 papers with code

UnitModule: A Lightweight Joint Image Enhancement Module for Underwater Object Detection

no code implementations9 Sep 2023 Zhuoyan Liu, Bo wang, Ye Li, Jiaxian He, Yunfeng Li

In this paper, we propose a plug-and-play Underwater joint image enhancement Module (UnitModule) that provides the input image preferred by the detector.

Data Augmentation Image Enhancement +2

OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting

1 code implementation4 Apr 2023 Xiao He, Ye Li, Jian Tan, Bin Wu, Feifei Li

Extensive experiments on real-world benchmark datasets for downstream time series anomaly detection and forecasting tasks demonstrate that OneShotSTL is from 10 to over 1, 000 times faster than the state-of-the-art methods, while still providing comparable or even better accuracy.

Anomaly Detection Time Series +1

DAA: A Delta Age AdaIN operation for age estimation via binary code transformer

no code implementations CVPR 2023 Ping Chen, Xingpeng Zhang, Ye Li, Ju Tao, Bin Xiao, Bing Wang, Zongjie Jiang

Inspired by the transfer learning, we designed the Delta Age AdaIN (DAA) operation to obtain the feature difference with each age, which obtains the style map of each age through the learned values representing the mean and standard deviation.

Age Estimation Transfer Learning

Implicit Stochastic Gradient Descent for Training Physics-informed Neural Networks

no code implementations3 Mar 2023 Ye Li, Song-Can Chen, Sheng-Jun Huang

Physics-informed neural networks (PINNs) have effectively been demonstrated in solving forward and inverse differential equation problems, but they are still trapped in training failures when the target functions to be approximated exhibit high-frequency or multi-scale features.

Interactive Log Parsing via Light-weight User Feedback

no code implementations28 Jan 2023 Liming Wang, Hong Xie, Ye Li, Jian Tan, John C. S. Lui

Template mining is one of the foundational tasks to support log analysis, which supports the diagnosis and troubleshooting of large scale Web applications.

Log Parsing

VQNet 2.0: A New Generation Machine Learning Framework that Unifies Classical and Quantum

no code implementations9 Jan 2023 Huanyu Bian, Zhilong Jia, Menghan Dou, Yuan Fang, Lei LI, Yiming Zhao, Hanchao Wang, Zhaohui Zhou, Wei Wang, Wenyu Zhu, Ye Li, Yang Yang, Weiming Zhang, Nenghai Yu, Zhaoyun Chen, Guoping Guo

Therefore, based on VQNet 1. 0, we further propose VQNet 2. 0, a new generation of unified classical and quantum machine learning framework that supports hybrid optimization.

Quantum Machine Learning Unity

Underwater Object Tracker: UOSTrack for Marine Organism Grasping of Underwater Vehicles

2 code implementations4 Jan 2023 Yunfeng Li, Bo wang, Ye Li, Zhuoyan Liu, Wei Huo, Yueming Li, Jian Cao

The UOHT training paradigm is designed to train the sample-imbalanced underwater tracker so that the tracker is exposed to a great number of underwater domain training samples and learns the feature expressions.

Data Augmentation object-detection +2

Investigation of Network Architecture for Multimodal Head-and-Neck Tumor Segmentation

no code implementations21 Dec 2022 Ye Li, Junyu Chen, Se-In Jang, Kuang Gong, Quanzheng Li

Inspired by the recent success of Transformers for Natural Language Processing and vision Transformer for Computer Vision, many researchers in the medical imaging community have flocked to Transformer-based networks for various main stream medical tasks such as classification, segmentation, and estimation.

Tumor Segmentation

Generative artificial intelligence-enabled dynamic detection of nicotine-related circuits

no code implementations13 Dec 2022 Changwei Gong, Changhong Jing, Ye Li, Xinan Liu, Zuxin Chen, Shuqiang Wang

And models of functional addiction circuits developed from functional imaging are an effective tool for discovering and verifying addiction circuits.

Contrastive Learning

Physics-guided Data Augmentation for Learning the Solution Operator of Linear Differential Equations

no code implementations8 Dec 2022 Ye Li, Yiwen Pang, Bin Shan

Neural networks, especially the recent proposed neural operator models, are increasingly being used to find the solution operator of differential equations.

Data Augmentation Translation

Bi-LSTM Price Prediction based on Attention Mechanism

no code implementations7 Dec 2022 Jiashu Lou, Leyi Cui, Ye Li

In this paper, we propose a bidirectional LSTM neural network based on an attention mechanism, which is based on two popular assets, gold and bitcoin.

Feature Engineering Time Series +1

VI-PINNs: Variance-involved Physics-informed Neural Networks for Fast and Accurate Prediction of Partial Differential Equations

1 code implementation30 Nov 2022 Bin Shan, Ye Li, Shengjun Huang

Although physics-informed neural networks(PINNs) have progressed a lot in many real applications recently, there remains problems to be further studied, such as achieving more accurate results, taking less training time, and quantifying the uncertainty of the predicted results.

Contextual Transformer for Offline Meta Reinforcement Learning

no code implementations15 Nov 2022 Runji Lin, Ye Li, Xidong Feng, Zhaowei Zhang, Xian Hong Wu Fung, Haifeng Zhang, Jun Wang, Yali Du, Yaodong Yang

Firstly, we propose prompt tuning for offline RL, where a context vector sequence is concatenated with the input to guide the conditional policy generation.

D4RL Meta Reinforcement Learning +4

Spach Transformer: Spatial and Channel-wise Transformer Based on Local and Global Self-attentions for PET Image Denoising

no code implementations7 Sep 2022 Se-In Jang, Tinsu Pan, Ye Li, Pedram Heidari, Junyu Chen, Quanzheng Li, Kuang Gong

In this work, we proposed an efficient spatial and channel-wise encoder-decoder transformer, Spach Transformer, that can leverage spatial and channel information based on local and global MSAs.

Image Denoising

LPC-AD: Fast and Accurate Multivariate Time Series Anomaly Detection via Latent Predictive Coding

no code implementations5 May 2022 Zhi Qi, Hong Xie, Ye Li, Jian Tan, Feifei Li, John C. S. Lui

LPC-AD is motivated by the ever-increasing needs for fast and accurate MTS anomaly detection methods to support fast troubleshooting in cloud computing, micro-service systems, etc.

Anomaly Detection Cloud Computing +2

A Noise-level-aware Framework for PET Image Denoising

no code implementations15 Mar 2022 Ye Li, Jianan Cui, Junyu Chen, Guodong Zeng, Scott Wollenweber, Floris Jansen, Se-In Jang, Kyungsang Kim, Kuang Gong, Quanzheng Li

Our hypothesis is that by explicitly providing the local relative noise level of the input image to a deep convolutional neural network (DCNN), the DCNN can outperform itself trained on image appearance only.

Image Denoising SSIM

Reinforcement Learning-Empowered Mobile Edge Computing for 6G Edge Intelligence

no code implementations27 Jan 2022 Peng Wei, Kun Guo, Ye Li, Jue Wang, Wei Feng, Shi Jin, Ning Ge, Ying-Chang Liang

Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive and delay-sensitive tasks in fifth generation (5G) networks and beyond.

Edge-computing reinforcement-learning +1

TransMorph: Transformer for unsupervised medical image registration

1 code implementation19 Nov 2021 Junyu Chen, Eric C. Frey, Yufan He, William P. Segars, Ye Li, Yong Du

Recently Vision Transformer architectures have been proposed to address the shortcomings of ConvNets and have produced state-of-the-art performances in many medical imaging applications.

Image Registration Medical Image Registration

ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration

1 code implementation13 Apr 2021 Junyu Chen, Yufan He, Eric C. Frey, Ye Li, Yong Du

However, the performances of ConvNets are still limited by lacking the understanding of long-range spatial relations in an image.

Image Classification Image Registration +3

A Multi-task Joint Framework for Real-time Person Search

no code implementations11 Dec 2020 Ye Li, Kangning Yin, Jie Liang, Chunyu Wang, Guangqiang Yin

To solve these problems, we propose a Multi-task Joint Framework for real-time person search (MJF), which optimizes the person detection, feature extraction and identity comparison respectively.

Human Detection Person Search

Discriminatively Constrained Semi-supervised Multi-view Nonnegative Matrix Factorization with Graph Regularization

no code implementations26 Oct 2020 Guosheng Cui, Ruxin Wang, Dan Wu, Ye Li

In recent years, semi-supervised multi-view nonnegative matrix factorization (MVNMF) algorithms have achieved promising performances for multi-view clustering.


Quality-aware semi-supervised learning for CMR segmentation

no code implementations1 Sep 2020 Bram Ruijsink, Esther Puyol-Anton, Ye Li, Wenja Bai, Eric Kerfoot, Reza Razavi, Andrew P. King

SemiQCSeg can be an efficient approach for training segmentation networks for medical image data when labelled datasets are scarce.

Data Augmentation Image Segmentation +2

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

4 code implementations ICLR 2021 Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, Arnold Overwijk

In this paper, we identify that the main bottleneck is in the training mechanisms, where the negative instances used in training are not representative of the irrelevant documents in testing.

Contrastive Learning Passage Retrieval +3

Boundary-aware Context Neural Network for Medical Image Segmentation

no code implementations3 May 2020 Ruxin Wang, Shuyuan Chen, Chaojie Ji, Jianping Fan, Ye Li

In this paper, we formulate a boundary-aware context neural network (BA-Net) for 2D medical image segmentation to capture richer context and preserve fine spatial information.

Image Segmentation Medical Image Segmentation +2

Cascaded Context Enhancement Network for Automatic Skin Lesion Segmentation

no code implementations17 Apr 2020 Ruxin Wang, Shuyuan Chen, Chaojie Ji, Ye Li

In this paper, we formulate a cascaded context enhancement neural network for automatic skin lesion segmentation.

Lesion Segmentation Melanoma Diagnosis +2

Triplet Online Instance Matching Loss for Person Re-identification

no code implementations24 Feb 2020 Ye Li, Guangqiang Yin, Chunhui Liu, Xiaoyu Yang, Zhiguo Wang

Triplet loss processes batch construction in a complicated and fussy way and converges slowly.

Person Re-Identification

Acoustic Scene Classification Using Bilinear Pooling on Time-liked and Frequency-liked Convolution Neural Network

no code implementations14 Feb 2020 Xing Yong Kek, Cheng Siong Chin, Ye Li

Although works have been done in using HPSS as input representation for CNN model in ASC task, this paper further investigate the possibility on leveraging the separated harmonic component and percussive component by curating 2 CNNs which tries to understand harmonic audio and percussive audio in their natural form, one specialized in extracting deep features in time biased domain and another specialized in extracting deep features in frequency biased domain, respectively.

Acoustic Scene Classification General Classification +4

Generating Anthropomorphic Phantoms Using Fully Unsupervised Deformable Image Registration with Convolutional Neural Networks

1 code implementation6 Dec 2019 Junyu Chen, Ye Li, Yong Du, Eric C. Frey

In this work, we present a novel image registration method for creating highly anatomically detailed anthropomorphic phantoms from a single digital phantom.

Anatomy Image Registration +2

Wearable Travel Aid for Environment Perception and Navigation of Visually Impaired People

no code implementations30 Apr 2019 Jinqiang Bai, Zhaoxiang Liu, Yimin Lin, Ye Li, Shiguo Lian, Dijun Liu

Based on the detected ground, the optimal walkable direction is computed and the user is then informed via converted beep sound.

Navigate object-detection +1

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