Peijie Yin

Achieving Fine-Grained QoS for Privacy-Aware Users in LBSs

Fenghua Li, Peijie Yin, Yahong Chen, 2020, IEEE Wireless Communications.

Improving learning efficiency of recurrent neural network through adjusting weights of all layers in a biologically-inspired framework

Peijie Yin, Hong Qiao, Xiao Huang, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Biologically inspired model simulating visual pathways and cerebellum function in human - Achieving visuomotor coordination and high precision movement with learning ability pdf

Peijie Yin, Hong Qiao, Jiahao Chen, 2016, ArXiv.

A biologically inspired model mimicking the memory and two distinct pathways of face perception

Peijie Yin, Hong Qiao, WenSen Feng, 2016, Neurocomputing.

NFLB dropout: Improve generalization ability by dropping out the best -A biologically inspired adaptive dropout method for unsupervised learning

Peijie Yin, Hong Qiao, Bo Zhang, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Robotics and Automation Activities in China [Industrial Activities]

Rui Li, Peijie Yin, Hong Qiao, 2015, IEEE Robotics Autom. Mag..

A Novel Biologically Inspired Visual Cognition Model: Automatic Extraction of Semantics, Formation of Integrated Concepts, and Reselection Features for Ambiguity

Peijie Yin, Hong Qiao, Bo Zhang, 2016, IEEE Transactions on Cognitive and Developmental Systems.

A Novel Biologically Mechanism-Based Visual Cognition Model--Automatic Extraction of Semantics, Formation of Integrated Concepts and Re-selection Features for Ambiguity

Wei Wu, Peijie Yin, Bo Zhang, 2016 .

Human-inspired motion model of upper-limb with fast response and learning ability – a promising direction for robot system and control

Peijie Yin, Hong Qiao, Chuan Li, 2016 .

Transfer classification for distinct manifestations with shared information

Ken Chen, Peijie Yin, Xiayuan Huang, 2016, 2016 12th World Congress on Intelligent Control and Automation (WCICA).