250 citations · 462 across the 30 of their papers we have counts for
4 papers · 1 filter
Learning a Generative Motion Model from Image Sequences based on a Latent Motion Matrix
Julian Krebs, Hervé Delingette, Nicholas Ayache +1
We propose to learn a probabilistic motion model from a sequence of images for spatio-temporal registration. Our model encodes motion in a low-dimensional probabilistic space - the…
Long Short-Term Memory Neuron Equalizer
Zihao Wang, Zhifei Xu, Jiayi He +3
In this work we propose a neuromorphic hardware based signal equalizer by based on the deep learning implementation. The proposed neural equalizer is plasticity trainable equalizer…
Quasi-symplectic Langevin Variational Autoencoder
Zihao Wang, Hervé Delingette
Variational autoencoder (VAE) is a very popular and well-investigated generative model in neural learning research. To leverage VAE in practical tasks dealing with a massive datase…
A Deep Learning based Fast Signed Distance Map Generation
Zihao Wang, Clair Vandersteen, Thomas Demarcy +4
Signed distance map (SDM) is a common representation of surfaces in medical image analysis and machine learning. The computational complexity of SDM for 3D parametric shapes is oft…