10 citations · 25 across the 8 of their papers we have counts for
9 papers
Revisiting Continual Semantic Segmentation with Pre-trained Vision Models
Duzhen Zhang, Yong Ren, Wei Cong +9
Continual Semantic Segmentation (CSS) seeks to incrementally learn to segment novel classes while preserving knowledge of previously encountered ones. Recent advancements in CSS ha…
MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graph
Duzhen Zhang, Zixiao Wang, Zhong-Zhi Li +10
The rapid expansion of medical literature challenges the scalable structuring of domain knowledge. Knowledge Graphs (KGs) offer a solution, yet current construction methods lack ge…
Tuning Synaptic Connections instead of Weights by Genetic Algorithm in Spiking Policy Network
Duzhen Zhang, Tielin Zhang, Shuncheng Jia +2
Learning from interaction is the primary way that biological agents acquire knowledge about their environment and themselves. Modern deep reinforcement learning (DRL) explores a co…
Motif-topology improved Spiking Neural Network for the Cocktail Party Effect and McGurk Effect
Shuncheng Jia, Tielin Zhang, Ruichen Zuo +1
Network architectures and learning principles are playing key in forming complex functions in artificial neural networks (ANNs) and spiking neural networks (SNNs). SNNs are conside…
Recent Advances and New Frontiers in Spiking Neural Networks
Duzhen Zhang, Shuncheng Jia, Qingyu Wang
In recent years, spiking neural networks (SNNs) have received extensive attention in brain-inspired intelligence due to their rich spatially-temporal dynamics, various encoding met…
Motif-topology and Reward-learning improved Spiking Neural Network for Efficient Multi-sensory Integration
Shuncheng Jia, Ruichen Zuo, Tielin Zhang +2
Network architectures and learning principles are key in forming complex functions in artificial neural networks (ANNs) and spiking neural networks (SNNs). SNNs are considered the…
Population-coding and Dynamic-neurons improved Spiking Actor Network for Reinforcement Learning
Duzhen Zhang, Tielin Zhang, Shuncheng Jia +2
With the Deep Neural Networks (DNNs) as a powerful function approximator, Deep Reinforcement Learning (DRL) has been excellently demonstrated on robotic control tasks. Compared to…
Finite Meta-Dynamic Neurons in Spiking Neural Networks for Spatio-temporal Learning
Xiang Cheng, Tielin Zhang, Shuncheng Jia +1
Spiking Neural Networks (SNNs) have incorporated more biologically-plausible structures and learning principles, hence are playing critical roles in bridging the gap between artifi…
Tuning Convolutional Spiking Neural Network with Biologically-plausible Reward Propagation
Tielin Zhang, Shuncheng Jia, Xiang Cheng +1
Spiking Neural Networks (SNNs) contain more biologically realistic structures and biologically-inspired learning principles than those in standard Artificial Neural Networks (ANNs)…