Search Results for author: Haifeng Li

Found 54 papers, 20 papers with code

Using Global Land Cover Product as Prompt for Cropland Mapping via Visual Foundation Model

no code implementations16 Oct 2023 Chao Tao, Aoran Hu, Rong Xiao, Haifeng Li, Yuze Wang

This simplifies the domain adaption from generic to specific scenes during model reasoning processes.

Domain Adaptation

AdaER: An Adaptive Experience Replay Approach for Continual Lifelong Learning

no code implementations7 Aug 2023 Xingyu Li, Bo Tang, Haifeng Li

Continual lifelong learning is an machine learning framework inspired by human learning, where learners are trained to continuously acquire new knowledge in a sequential manner.

Class Incremental Learning Incremental Learning

BCE-Net: Reliable Building Footprints Change Extraction based on Historical Map and Up-to-Date Images using Contrastive Learning

1 code implementation14 Apr 2023 Cheng Liao, Han Hu, Xuekun Yuan, Haifeng Li, Chao Liu, Chunyang Liu, Gui Fu, Yulin Ding, Qing Zhu

This contrastive learning strategy allowed us to inject the semantics of buildings into a pipeline for the detection of changes, which is achieved by increasing the distinguishability of features of buildings from those of non-buildings.

Change Detection Contrastive Learning

False: False Negative Samples Aware Contrastive Learning for Semantic Segmentation of High-Resolution Remote Sensing Image

1 code implementation15 Nov 2022 Zhaoyang Zhang, Xuying Wang, Xiaoming Mei, Chao Tao, Haifeng Li

This indicates that the SSCL model has the ability to self-differentiate FNS and that the FALSE effectively mitigates the SCI in self-supervised contrastive learning.

Contrastive Learning Segmentation +1

Self-supervised remote sensing feature learning: Learning Paradigms, Challenges, and Future Works

no code implementations15 Nov 2022 Chao Tao, Ji Qi, Mingning Guo, Qing Zhu, Haifeng Li

Deep learning has achieved great success in learning features from massive remote sensing images (RSIs).

STGC-GNNs: A GNN-based traffic prediction framework with a spatial-temporal Granger causality graph

no code implementations30 Oct 2022 Silu He, Qinyao Luo, Ronghua Du, Ling Zhao, Haifeng Li

We further propose spatial-temporal Granger causality (STGC) to express TCR, which models global and dynamic spatial dependence.

Traffic Prediction

TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-supervised Learning

1 code implementation10 Apr 2022 Chao Tao, Ji Qia, Guo Zhang, Qing Zhu, Weipeng Lu, Haifeng Li

We believe that a general model which is trained by a label-free and task-independent way may be the next paradigm for RSIU and hope the insights distilled from this study can help to foster the development of an original vision model for RSIU.

General Knowledge object-detection +4

Overcome Anterograde Forgetting with Cycled Memory Networks

no code implementations4 Dec 2021 Jian Peng, Dingqi Ye, Bo Tang, Yinjie Lei, Yu Liu, Haifeng Li

This work proposes a general framework named Cycled Memory Networks (CMN) to address the anterograde forgetting in neural networks for lifelong learning.

Transfer Learning

Reviewing continual learning from the perspective of human-level intelligence

no code implementations23 Nov 2021 Yifan Chang, Wenbo Li, Jian Peng, Bo Tang, Yu Kang, Yinjie Lei, Yuanmiao Gui, Qing Zhu, Yu Liu, Haifeng Li

Different from previous reviews that mainly focus on the catastrophic forgetting phenomenon in CL, this paper surveys CL from a more macroscopic perspective based on the Stability Versus Plasticity mechanism.

Continual Learning

Learning by Active Forgetting for Neural Networks

no code implementations21 Nov 2021 Jian Peng, Xian Sun, Min Deng, Chao Tao, Bo Tang, Wenbo Li, Guohua Wu, QingZhu, Yu Liu, Tao Lin, Haifeng Li

This paper presents a learning model by active forgetting mechanism with artificial neural networks.

Curvature Graph Neural Network

no code implementations30 Jun 2021 Haifeng Li, Jun Cao, Jiawei Zhu, Yu Liu, Qing Zhu, Guohua Wu

And we propose Curvature Graph Neural Network (CGNN), which effectively improves the adaptive locality ability of GNNs by leveraging the structural property of graph curvature.

Node Classification

Global and Local Contrastive Self-Supervised Learning for Semantic Segmentation of HR Remote Sensing Images

1 code implementation20 Jun 2021 Haifeng Li, Yi Li, Guo Zhang, Ruoyun Liu, Haozhe Huang, Qing Zhu, Chao Tao

Supervised learning for semantic segmentation requires a large number of labeled samples, which is difficult to obtain in the field of remote sensing.

Contrastive Learning Segmentation +2

Generating Multi-scale Maps from Remote Sensing Images via Series Generative Adversarial Networks

no code implementations31 Mar 2021 Xu Chen, Bangguo Yin, Songqiang Chen, Haifeng Li, Tian Xu

The series strategy avoids RS-m inconsistency as inputs are high-resolution large-scale RSIs, and reduces the distribution gap in multi-scale map generation through similar pixel distributions among multi-scale maps.

Image-to-Image Translation Translation

Graph Information Vanishing Phenomenon inImplicit Graph Neural Networks

no code implementations2 Mar 2021 Haifeng Li, Jun Cao, Jiawei Zhu, Qing Zhu, Guohua Wu

A class of GNNs solves this problem by learning implicit weights to represent the importance of neighbor nodes, which we call implicit GNNs such as Graph Attention Network.

Graph Attention

On Training Effective Reinforcement Learning Agents for Real-time Power Grid Operation and Control

no code implementations11 Dec 2020 Ruisheng Diao, Di Shi, Bei Zhang, Siqi Wang, Haifeng Li, Chunlei Xu, Tu Lan, Desong Bian, Jiajun Duan

Deriving fast and effectively coordinated control actions remains a grand challenge affecting the secure and economic operation of today's large-scale power grid.

Optimization and Control Systems and Control Systems and Control

KST-GCN: A Knowledge-Driven Spatial-Temporal Graph Convolutional Network for Traffic Forecasting

1 code implementation26 Nov 2020 Jiawei Zhu, Xin Han, Hanhan Deng, Chao Tao, Ling Zhao, Pu Wang, Lin Tao, Haifeng Li

On this background, this study presents a knowledge representation-driven traffic forecasting method based on spatial-temporal graph convolutional networks.

Knowledge Graphs Representation Learning

Depth-Enhanced Feature Pyramid Network for Occlusion-Aware Verification of Buildings from Oblique Images

no code implementations26 Nov 2020 Qing Zhu, Shengzhi Huang, Han Hu, Haifeng Li, Min Chen, Ruofei Zhong

Finally, multi-view information from both the nadir and oblique images is used in a robust voting procedure to label changes in existing buildings.

Hierarchical Paired Channel Fusion Network for Street Scene Change Detection

no code implementations19 Oct 2020 Yinjie Lei, Duo Peng, Pingping Zhang, Qiuhong Ke, Haifeng Li

Based on the MPFL strategy, our framework achieves a novel approach to adapt to the scale and location diversities of the scene change regions.

Change Detection Scene Change Detection

Remote Sensing Image Scene Classification with Self-Supervised Paradigm under Limited Labeled Samples

no code implementations2 Oct 2020 Chao Tao, Ji Qi, Weipeng Lu, Hao Wang, Haifeng Li

With the development of deep learning, supervised learning methods perform well in remote sensing images (RSIs) scene classification.

Classification General Classification +2

RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification

no code implementations28 Sep 2020 Haifeng Li, Zhenqi Cui, Zhiqing Zhu, Li Chen, Jiawei Zhu, Haozhe Huang, Chao Tao

On the one hand, RS-MetaNet raises the level of learning from the sample to the task by organizing training in a meta way, and it learns to learn a metric space that can well classify remote sensing scenes from a series of tasks.

General Classification Metric Learning +1

Urban Traffic Flow Forecast Based on FastGCRNN

no code implementations17 Sep 2020 Ya Zhang, Mingming Lu, Haifeng Li

Traffic forecasting is an important prerequisite for the application of intelligent transportation systems in urban traffic networks.

Bottom-up mechanism and improved contract net protocol for the dynamic task planning of heterogeneous Earth observation resources

no code implementations13 Jul 2020 Baoju Liu, Min Deng, Guohua Wu, Xinyu Pei, Haifeng Li, Witold Pedrycz

It also demonstrates that this method can help to efficiently obtain replanning schemes based on original scheme in dynamic environments.

A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting

2 code implementations20 Jun 2020 Jiawei Zhu, Yujiao Song, Ling Zhao, Haifeng Li

In this study, an attention temporal graph convolutional network (A3T-GCN) traffic forecasting method was proposed to simultaneously capture global temporal dynamics and spatial correlations.

Time Series Time Series Analysis

DAPnet: A Double Self-attention Convolutional Network for Point Cloud Semantic Labeling

1 code implementation18 Apr 2020 Li Chen, Zewei Xu, Yongjian Fu, Haozhe Huang, Shaowen Wang, Haifeng Li

The incorporation of the double self-attention module has an average of 7\% improvement on the pre-class accuracy.

Deep Fusion of Local and Non-Local Features for Precision Landslide Recognition

1 code implementation20 Feb 2020 Qing Zhu, Lin Chen, Han Hu, Binzhi Xu, Yeting Zhang, Haifeng Li

The second uses a scale attention mechanism to guide the up-sampling of features from the coarse level by a learned weight map.

Semantic Segmentation

SCAttNet: Semantic Segmentation Network with Spatial and Channel Attention Mechanism for High-Resolution Remote Sensing Images

1 code implementation19 Dec 2019 Haifeng Li, Kaijian Qiu, Li Chen, Xiaoming Mei, Liang Hong, Chao Tao

High-resolution remote sensing images (HRRSIs) contain substantial ground object information, such as texture, shape, and spatial location.

Segmentation Semantic Segmentation

Overcoming Long-term Catastrophic Forgetting through Adversarial Neural Pruning and Synaptic Consolidation

1 code implementation19 Dec 2019 Jian Peng, Bo Tang, Hao Jiang, Zhuo Li, Yinjie Lei, Tao Lin, Haifeng Li

It is due to two facts: first, as the model learns more tasks, the intersection of the low-error parameter subspace satisfying for these tasks becomes smaller or even does not exist; second, when the model learns a new task, the cumulative error keeps increasing as the model tries to protect the parameter configuration of previous tasks from interference.

Image Classification

Adversarial Example in Remote Sensing Image Recognition

no code implementations29 Oct 2019 Li Chen, Guowei Zhu, Qi Li, Haifeng Li

This added adversarial perturbation image is called an adversarial example, which poses a serious security problem for systems based on CNN model recognition results.

Spatial Information Inference Net: Road Extraction Using Road-Specific Contextual Information

1 code implementation ISPRS Journal of Photogrammetry and Remote Sensing 2019 Chao Tao, Ji Qi, Yansheng Li, Hao Wang, Haifeng Li

The validation experiments using three large datasets of very high-resolution (VHR) satellite imagery show that the proposed method can improve road extraction accuracy and provide an output that is more in line with human expectations.

Road Segmentation Segmentation

MAP-Net: Multi Attending Path Neural Network for Building Footprint Extraction from Remote Sensed Imagery

1 code implementation26 Oct 2019 Qing Zhu, Cheng Liao, Han Hu, Xiaoming Mei, Haifeng Li

This paper proposes a novel multi attending path neural network (MAP-Net) for accurately extracting multiscale building footprints and precise boundaries.

Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis

no code implementations26 Mar 2019 Yayu Peng, Yishen Wang, Xiao Lu, Haifeng Li, Di Shi, Zhiwei Wang, Jie Li

Short-term load forecasting (STLF) is essential for the reliable and economic operation of power systems.

Load Forecasting

Probabilistic Load Forecasting via Point Forecast Feature Integration

no code implementations26 Mar 2019 Qicheng Chang, Yishen Wang, Xiao Lu, Di Shi, Haifeng Li, Jiajun Duan, Zhiwei Wang

In the first stage, all related features are utilized to train a point forecast model and also obtain the feature importance.

energy management Feature Importance +3

Program Classification Using Gated Graph Attention Neural Network for Online Programming Service

no code implementations9 Mar 2019 Mingming Lu, Dingwu Tan, Naixue Xiong, Zailiang Chen, Haifeng Li

The online programing services, such as Github, TopCoder, and EduCoder, have promoted a lot of social interactions among the service users.

General Classification Graph Attention

Understanding the Importance of Single Directions via Representative Substitution

no code implementations20 Jan 2019 Li Chen, Hailun Ding, Qi Li, Zhuo Li, Jian Peng, Haifeng Li

Understanding the internal representations of deep neural networks (DNNs) is crucal to explain their behavior.

A Data-driven Adversarial Examples Recognition Framework via Adversarial Feature Genome

no code implementations25 Dec 2018 Li Chen, Qi Li, Weiye Chen, Zeyu Wang, Haifeng Li

In this regard, we propose the Adversarial Feature Genome (AFG), a novel type of data that contains both the differences and features about classes.

General Classification Multi-Label Classification

Overcoming Catastrophic Forgetting by Soft Parameter Pruning

1 code implementation4 Dec 2018 Jian Peng, Jiang Hao, Zhuo Li, Enqiang Guo, Xiaohong Wan, Deng Min, Qing Zhu, Haifeng Li

In this paper, we proposed a Soft Parameters Pruning (SPP) strategy to reach the trade-off between short-term and long-term profit of a learning model by freeing those parameters less contributing to remember former task domain knowledge to learn future tasks, and preserving memories about previous tasks via those parameters effectively encoding knowledge about tasks at the same time.

Continual Learning

Understanding the Importance of Single Directions via Representative Substitution

no code implementations27 Nov 2018 Li Chen, Hailun Ding, Qi Li, Zhuo Li, Jian Peng, Haifeng Li

Understanding the internal representations of deep neural networks (DNNs) is crucal to explain their behavior.

T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction

9 code implementations12 Nov 2018 Ling Zhao, Yujiao Song, Chao Zhang, Yu Liu, Pu Wang, Tao Lin, Min Deng, Haifeng Li

However, traffic forecasting has always been considered an open scientific issue, owing to the constraints of urban road network topological structure and the law of dynamic change with time, namely, spatial dependence and temporal dependence.

Management Traffic Prediction

Learning to Measure Change: Fully Convolutional Siamese Metric Networks for Scene Change Detection

2 code implementations22 Oct 2018 Enqiang Guo, Xinsha Fu, Jiawei Zhu, Min Deng, Yu Liu, Qing Zhu, Haifeng Li

A critical challenge problem of scene change detection is that noisy changes generated by varying illumination, shadows and camera viewpoint make variances of a scene difficult to define and measure since the noisy changes and semantic ones are entangled.

Change Detection Scene Change Detection

On the Selective and Invariant Representation of DCNN for High-Resolution Remote Sensing Image Recognition

no code implementations4 Aug 2017 Jie Chen, Chao Yuan, Min Deng, Chao Tao, Jian Peng, Haifeng Li

Owing to its superiority in feature representation, DCNN has exhibited remarkable performance in scene recognition of high-resolution remote sensing (HRRS) images and classification of hyper-spectral remote sensing images.

General Classification Scene Recognition

RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource Data

1 code implementation30 May 2017 Haifeng Li, Xin Dou, Chao Tao, Zhixiang Hou, Jie Chen, Jian Peng, Min Deng, Ling Zhao

In this paper, we propose a remote sensing image classification benchmark (RSI-CB) based on massive, scalable, and diverse crowdsource data.

Classification General Classification +2

What do We Learn by Semantic Scene Understanding for Remote Sensing imagery in CNN framework?

no code implementations19 May 2017 Haifeng Li, Jian Peng, Chao Tao, Jie Chen, Min Deng

Is the DCNN recognition mechanism centered on object recognition still applicable to the scenarios of remote sensing scene understanding?

Object Recognition Scene Recognition +1

An adaptive Simulated Annealing-based satellite observation scheduling method combined with a dynamic task clustering strategy

no code implementations14 Jan 2014 Guohua Wu, Huilin Wang, Haifeng Li, Witold Pedrycz, Dishan Qiu, Manhao Ma, Jin Liu

In this study, we present an adaptive Simulated Annealing based scheduling algorithm aggregated with a dynamic task clustering strategy (or ASA-DTC for short) for satellite observation scheduling problems (SOSPs).

Clustering Scheduling

Cannot find the paper you are looking for? You can Submit a new open access paper.