10 citations · 11 across the 6 of their papers we have counts for
6 papers
Training Robust Spiking Neural Networks with ViewPoint Transform and SpatioTemporal Stretching
Haibo Shen, Juyu Xiao, Yihao Luo +3
Neuromorphic vision sensors (event cameras) simulate biological visual perception systems and have the advantages of high temporal resolution, less data redundancy, low power consu…
Frequency and Scale Perspectives of Feature Extraction
Liangqi Zhang, Yihao Luo, Xiang Cao +2
Convolutional neural networks (CNNs) have achieved superior performance but still lack clarity about the nature and properties of feature extraction. In this paper, by analyzing th…
Efficient CNN Architecture Design Guided by Visualization
Liangqi Zhang, Haibo Shen, Yihao Luo +4
Modern efficient Convolutional Neural Networks(CNNs) always use Depthwise Separable Convolutions(DSCs) and Neural Architecture Search(NAS) to reduce the number of parameters and th…
Training Stronger Spiking Neural Networks with Biomimetic Adaptive Internal Association Neurons
Haibo Shen, Yihao Luo, Xiang Cao +3
As the third generation of neural networks, spiking neural networks (SNNs) are dedicated to exploring more insightful neural mechanisms to achieve near-biological intelligence. Int…
Training Robust Spiking Neural Networks on Neuromorphic Data with Spatiotemporal Fragments
Haibo Shen, Yihao Luo, Xiang Cao +3
Neuromorphic vision sensors (event cameras) are inherently suitable for spiking neural networks (SNNs) and provide novel neuromorphic vision data for this biomimetic model. Due to…
CE-FPN: Enhancing Channel Information for Object Detection
Yihao Luo, Xiang Cao, Juntao Zhang +4
Feature pyramid network (FPN) has been an effective framework to extract multi-scale features in object detection. However, current FPN-based methods mostly suffer from the intrins…