29 citations · 41 across the 5 of their papers we have counts for
5 papers
LSEC: Large-scale spectral ensemble clustering
Hongmin Li, Xiucai Ye, Akira Imakura +1
Ensemble clustering is a fundamental problem in the machine learning field, combining multiple base clusterings into a better clustering result. However, most of the existing metho…
Divide-and-conquer based Large-Scale Spectral Clustering
Hongmin Li, Xiucai Ye, Akira Imakura +1
Spectral clustering is one of the most popular clustering methods. However, how to balance the efficiency and effectiveness of the large-scale spectral clustering with limited comp…
Robust event-stream pattern tracking based on correlative filter
Hongmin Li, Luping Shi
Object tracking based on retina-inspired and event-based dynamic vision sensor (DVS) is challenging for the noise events, rapid change of event-stream shape, chaos of complex backg…
Super-resolution of spatiotemporal event-stream image captured by the asynchronous temporal contrast vision sensor
Hongmin Li, Guoqi Li, Hanchao Liu +1
Super-resolution (SR) is a useful technology to generate a high-resolution (HR) visual output from the low-resolution (LR) visual inputs overcoming the physical limitations of the…
Real-time Tracking Based on Neuromrophic Vision
Hongmin Li, Pei Jing, Guoqi Li
Real-time tracking is an important problem in computer vision in which most methods are based on the conventional cameras. Neuromorphic vision is a concept defined by incorporating…