Liu Liu

According to our database, Liu Liu authored at least 22 papers between 2019 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Toward Real-World Category-Level Articulation Pose Estimation.

Liu Liu, Han Xue, Wenqiang Xu, Haoyuan Fu, Cewu Lu

IEEE Trans. Image Process., 2022

When Pansharpening Meets Graph Convolution Network and Knowledge Distillation.

Keyu Yan, Man Zhou, Liu Liu, Chengjun Xie, Danfeng Hong

IEEE Trans. Geosci. Remote. Sens., 2022

A global activated feature pyramid network for tiny pest detection in the wild.

Liu Liu, Rujing Wang, Chengjun Xie, Rui Li, Fangyuan Wang, Long Qi

Mach. Vis. Appl., 2022

Towards densely clustered tiny pest detection in the wild environment.

Jianming Du, Liu Liu, Rui Li, Lin Jiao, Chengjun Xie, Rujing Wang

Neurocomputing, 2022

AKB-48: A Real-World Articulated Object Knowledge Base.

Liu Liu, Wenqiang Xu, Haoyuan Fu, Sucheng Qian, Yang Han, Cewu Lu

CoRR, 2022

OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object Interaction.

Lixin Yang, Kailin Li, Xinyu Zhan, Fei Wu, Anran Xu, Liu Liu, Cewu Lu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

AKB-48: A Real-World Articulated Object Knowledge Base.

Liu Liu, Wenqiang Xu, Haoyuan Fu, Sucheng Qian, Qiaojun Yu, Yang Han, Cewu Lu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Deep Learning Based Automatic Multiclass Wild Pest Monitoring Approach Using Hybrid Global and Local Activated Features.

Liu Liu, Chengjun Xie, Rujing Wang, Po Yang, Sud Sudirman, Jie Zhang, Rui Li, Fangyuan Wang

IEEE Trans. Ind. Informatics, 2021

AgriPest: A Large-Scale Domain-Specific Benchmark Dataset for Practical Agricultural Pest Detection in the Wild.

Rujing Wang, Liu Liu, Chengjun Xie, Po Yang, Rui Li, Man Zhou

Sensors, 2021

GSS-RiskAsser: A Multi-Modal Deep-Learning Framework for Urban Gas Supply System Risk Assessment on Business Users.

Xuefei Li, Liangtu Song, Liu Liu, Linli Zhou

Sensors, 2021

Learning region-guided scale-aware feature selection for object detection.

Liu Liu, Rujing Wang, Chengjun Xie, Rui Li, Fangyuan Wang, Man Zhou, Yue Teng

Neural Comput. Appl., 2021

ReinforceNet: A reinforcement learning embedded object detection framework with region selection network.

Man Zhou, Rujing Wang, Chengjun Xie, Liu Liu, Rui Li, Fangyuan Wang, Dengshan Li

Neurocomputing, 2021

Convolutional neural network based automatic pest monitoring system using hand-held mobile image analysis towards non-site-specific wild environment.

Fangyuan Wang, Rujing Wang, Chengjun Xie, Jie Zhang, Rui Li, Liu Liu

Comput. Electron. Agric., 2021

Reinforcedet: Object Detection By Integrating Reinforcement Learning With Decoupled Pipeline.

Man Zhou, Liu Liu, Rujing Wang

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

2020

A Recognition Method for Rice Plant Diseases and Pests Video Detection Based on Deep Convolutional Neural Network.

Dengshan Li, Rujing Wang, Chengjun Xie, Liu Liu, Jie Zhang, Rui Li, Fangyuan Wang, Man Zhou, Wancai Liu

Sensors, 2020

Fusing multi-scale context-aware information representation for automatic in-field pest detection and recognition.

Fangyuan Wang, Rujing Wang, Chengjun Xie, Po Yang, Liu Liu

Comput. Electron. Agric., 2020

An effective automatic system deployed in agricultural Internet of Things using Multi-Context Fusion Network towards crop disease recognition in the wild.

Yushan Zhao, Liu Liu, Chengjun Xie, Rujing Wang, Fangyuan Wang, Yingqiao Bu, Shunxiang Zhang

Appl. Soft Comput., 2020

FPHA-Afford: A Domain-Specific Benchmark Dataset for Occluded Object Affordance Estimation in Human-Object-Robot Interaction.

S. Muzamil Hussain, Liu Liu, Wenqiang Xu, Cewu Lu

Proceedings of the IEEE International Conference on Image Processing, 2020

2019

A Deep Learning Framework for Driving Behavior Identification on In-Vehicle CAN-BUS Sensor Data.

Jun Zhang, ZhongCheng Wu, Fang Li, Chengjun Xie, Tingting Ren, Jie Chen, Liu Liu

Sensors, 2019

PestNet: An End-to-End Deep Learning Approach for Large-Scale Multi-Class Pest Detection and Classification.

Liu Liu, Rujing Wang, Chengjun Xie, Po Yang, Fangyuan Wang, Sud Sudirman, Wancai Liu

IEEE Access, 2019

An Effective Data Augmentation Strategy for CNN-Based Pest Localization and Recognition in the Field.

Rui Li, Xiufang Jia, Min Hu, Man Zhou, Dengshan Li, Wancai Liu, Rujing Wang, Jie Zhang, Chengjun Xie, Liu Liu, Fangyuan Wang, Hongbo Chen, Tianjiao Chen, Haiying Hu

IEEE Access, 2019

Deep Learning based Automatic Approach using Hybrid Global and Local Activated Features towards Large-scale Multi-class Pest Monitoring.

Liu Liu, Rujing Wang, Chengjun Xie, Po Yang, Sud Sudirman, Fangyuan Wang, Rui Li

Proceedings of the 17th IEEE International Conference on Industrial Informatics, 2019