Search Results for author: Lin Zhu

Found 26 papers, 8 papers with code

Data-Driven Fast Frequency Control using Inverter-Based Resources

no code implementations11 Apr 2023 Etinosa Ekomwenrenren, John W. Simpson-Porco, Evangelos Farantatos, Mahendra Patel, Aboutaleb Haddadi, Lin Zhu

To address the control challenges associated with the increasing share of inverter-connected renewable energy resources, this paper proposes a direct data-driven approach for fast frequency control in the bulk power system.

Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric

1 code implementation20 Nov 2022 Chuanming Tang, Xiao Wang, Ju Huang, Bo Jiang, Lin Zhu, Jianlin Zhang, YaoWei Wang, Yonghong Tian

In this paper, we propose a single-stage backbone network for Color-Event Unified Tracking (CEUTrack), which achieves the above functions simultaneously.

Object Localization Object Tracking

HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors

2 code implementations17 Nov 2022 Xiao Wang, Zongzhen Wu, Bo Jiang, Zhimin Bao, Lin Zhu, Guoqi Li, YaoWei Wang, Yonghong Tian

The main streams of human activity recognition (HAR) algorithms are developed based on RGB cameras which are suffered from illumination, fast motion, privacy-preserving, and large energy consumption.

Activity Prediction Human Activity Recognition +1

Unsupervised Deraining: Where Asymmetric Contrastive Learning Meets Self-similarity

no code implementations2 Nov 2022 Yi Chang, Yun Guo, Yuntong Ye, Changfeng Yu, Lin Zhu, XiLe Zhao, Luxin Yan, Yonghong Tian

In addition, considering that the existing real rain datasets are of low quality, either small scale or downloaded from the internet, we collect a real large-scale dataset under various rainy kinds of weather that contains high-resolution rainy images.

Contrastive Learning Rain Removal

Data-Driven Fast Frequency Control using Inverter-Based Resources

no code implementations2 Aug 2022 Etinosa Ekomwenrenren, John Simpson-Porco, Evangelos Farantatos, Mahendra Patel, Aboutaleb Haddadi, Lin Zhu

We develop and test a data-driven and area-based fast frequency control scheme, which rapidly redispatches inverter-based resources to compensate for local power imbalances within the bulk power system.

Mirror Complementary Transformer Network for RGB-thermal Salient Object Detection

1 code implementation7 Jul 2022 Xiurong Jiang, Lin Zhu, Yifan Hou, Hui Tian

Thus, the key problem of RGB-T SOD is to make the features from the two modalities complement and adjust each other flexibly, since it is inevitable that any modalities of RGB-T image pairs failure due to challenging scenes such as extreme light conditions and thermal crossover.

Autonomous Driving object-detection +3

Noise and Edge Based Dual Branch Image Manipulation Detection

1 code implementation2 Jul 2022 Zhongyuan Zhang, Yi Qian, Yanxiang Zhao, Lin Zhu, Jinjin Wang

In this paper, the noise image extracted by the improved constrained convolution is used as the input of the model instead of the original image to obtain more subtle traces of manipulation.

Edge Detection Image Manipulation +1

Prompt-based Learning for Unpaired Image Captioning

no code implementations26 May 2022 Peipei Zhu, Xiao Wang, Lin Zhu, Zhenglong Sun, Weishi Zheng, YaoWei Wang, Changwen Chen

Inspired by the success of Vision-Language Pre-Trained Models (VL-PTMs) in this research, we attempt to infer the cross-domain cue information about a given image from the large VL-PTMs for the UIC task.

Image Captioning Question Answering +2

Network Topology Optimization via Deep Reinforcement Learning

no code implementations19 Apr 2022 Zhuoran Li, Xing Wang, Ling Pan, Lin Zhu, Zhendong Wang, Junlan Feng, Chao Deng, Longbo Huang

A2C-GS consists of three novel components, including a verifier to validate the correctness of a generated network topology, a graph neural network (GNN) to efficiently approximate topology rating, and a DRL actor layer to conduct a topology search.

Management reinforcement-learning +1

Event-based Video Reconstruction via Potential-assisted Spiking Neural Network

no code implementations CVPR 2022 Lin Zhu, Xiao Wang, Yi Chang, Jianing Li, Tiejun Huang, Yonghong Tian

We propose a novel Event-based Video reconstruction framework based on a fully Spiking Neural Network (EVSNN), which utilizes Leaky-Integrate-and-Fire (LIF) neuron and Membrane Potential (MP) neuron.

Image Reconstruction Video Reconstruction

1000x Faster Camera and Machine Vision with Ordinary Devices

no code implementations23 Jan 2022 Tiejun Huang, Yajing Zheng, Zhaofei Yu, Rui Chen, Yuan Li, Ruiqin Xiong, Lei Ma, Junwei Zhao, Siwei Dong, Lin Zhu, Jianing Li, Shanshan Jia, Yihua Fu, Boxin Shi, Si Wu, Yonghong Tian

By treating vidar as spike trains in biological vision, we have further developed a spiking neural network-based machine vision system that combines the speed of the machine and the mechanism of biological vision, achieving high-speed object detection and tracking 1, 000x faster than human vision.

object-detection Object Detection

Adaptive Multi-receptive Field Spatial-Temporal Graph Convolutional Network for Traffic Forecasting

no code implementations1 Nov 2021 Xing Wang, Juan Zhao, Lin Zhu, Xu Zhou, Zhao Li, Junlan Feng, Chao Deng, Yong Zhang

AMF-STGCN extends GCN by (1) jointly modeling the complex spatial-temporal dependencies in mobile networks, (2) applying attention mechanisms to capture various Receptive Fields of heterogeneous base stations, and (3) introducing an extra decoder based on a fully connected deep network to conquer the error propagation challenge with multi-step forecasting.

VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows

2 code implementations11 Aug 2021 Xiao Wang, Jianing Li, Lin Zhu, Zhipeng Zhang, Zhe Chen, Xin Li, YaoWei Wang, Yonghong Tian, Feng Wu

Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lower latency.

Object Tracking

NeuSpike-Net: High Speed Video Reconstruction via Bio-Inspired Neuromorphic Cameras

no code implementations ICCV 2021 Lin Zhu, Jianing Li, Xiao Wang, Tiejun Huang, Yonghong Tian

In this paper, we propose a NeuSpike-Net to learn both the high dynamic range and high motion sensitivity of DVS and the full texture sampling of spike camera to achieve high-speed and high dynamic image reconstruction.

Image Reconstruction Video Reconstruction +1

GenAD: General Representations of Multivariate Time Series for Anomaly Detection

no code implementations1 Jan 2021 Xiaolei Hua, Su Wang, Lin Zhu, Dong Zhou, Junlan Feng, Yiting Wang, Chao Deng, Shuo Wang, Mingtao Mei

However, due to complex correlations and various temporal patterns of large-scale multivariate time series, a general unsupervised anomaly detection model with higher F1-score and Timeliness remains a challenging task.

Management Time Series Analysis +1

Adaptive Spatial-Temporal Inception Graph Convolutional Networks for Multi-step Spatial-Temporal Network Data Forecasting

no code implementations1 Jan 2021 Xing Wang, Lin Zhu, Juan Zhao, Zhou Xu, Zhao Li, Junlan Feng, Chao Deng

Spatial-temporal data forecasting is of great importance for industries such as telecom network operation and transportation management.


Retina-Like Visual Image Reconstruction via Spiking Neural Model

no code implementations CVPR 2020 Lin Zhu, Siwei Dong, Jianing Li, Tiejun Huang, Yonghong Tian

The experimental results show that the proposed approach is extremely effective in reconstructing the visual image in both normal and high speed scenes, while achieving high dynamic range and high image quality.

Image Reconstruction

Algebraic Operations on Spatiotemporal Data Based on RDF

no code implementations ISPRS Int. J. Geo-Inf. 2020 Lin Zhu, Nan Li and Luyi Bai

The algebraic approach has been proven to be an effective way to process queries, and algebraic operations in RDF have been investigated extensively.

A Retina-inspired Sampling Method for Visual Texture Reconstruction

no code implementations20 Jul 2019 Lin Zhu, Siwei Dong, Tiejun Huang, Yonghong Tian

Conventional frame-based camera is not able to meet the demand of rapid reaction for real-time applications, while the emerging dynamic vision sensor (DVS) can realize high speed capturing for moving objects.

HDI-Forest: Highest Density Interval Regression Forest

2 code implementations24 May 2019 Lin Zhu, Jiaxing Lu, Yihong Chen

By seeking the narrowest prediction intervals (PIs) that satisfy the specified coverage probability requirements, the recently proposed quality-based PI learning principle can extract high-quality PIs that better summarize the predictive certainty in regression tasks, and has been widely applied to solve many practical problems.

Prediction Intervals regression

Session-based Sequential Skip Prediction via Recurrent Neural Networks

no code implementations13 Feb 2019 Lin Zhu, Yihong Chen

The focus of WSDM cup 2019 is session-based sequential skip prediction, i. e. predicting whether users will skip tracks, given their immediately preceding interactions in their listening session.

Sequential skip prediction Session-Based Recommendations

A Domain Generalization Perspective on Listwise Context Modeling

no code implementations12 Feb 2019 Lin Zhu, Yihong Chen, Bowen He

As one of the most popular techniques for solving the ranking problem in information retrieval, Learning-to-rank (LETOR) has received a lot of attention both in academia and industry due to its importance in a wide variety of data mining applications.

Domain Generalization Information Retrieval +2

A Graph-Based Semi-Supervised k Nearest-Neighbor Method for Nonlinear Manifold Distributed Data Classification

no code implementations3 Jun 2016 Enmei Tu, Yaqian Zhang, Lin Zhu, Jie Yang, Nikola Kasabov

In this paper, we propose a new graph-based $k$NN algorithm which can effectively handle both Gaussian distributed data and nonlinear manifold distributed data.

General Classification

Robust and Efficient Subspace Segmentation via Least Squares Regression

1 code implementation27 Apr 2014 Can-Yi Lu, Hai Min, Zhong-Qiu Zhao, Lin Zhu, De-Shuang Huang, Shuicheng Yan

If the subspaces from which the data drawn are independent or orthogonal, they are able to obtain a block diagonal affinity matrix, which usually leads to a correct segmentation.


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