Reformulating Level Sets as Deep Recurrent Neural Network Approach to
Semantic Segmentation

Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation

12 April 2017

Ngan Le

Marios Savvides

Papers citing "Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation"

8 / 8 papers shown

Title
Machine learning algorithms for three-dimensional mean-curvature computation in the level-set method Luis Ángel Larios-Cárdenas Frédéric Gibou 3DV 17 1 0 18 Aug 2022
OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptation Thanh-Dat Truong N. V. R. Chappa Xuan-Bac Nguyen Ngan Le Ashley Dowling Khoa Luu OOD OT 34 11 0 22 May 2022
Self-Ensembling GAN for Cross-Domain Semantic Segmentation Yonghao Xu Fengxiang He Bo Du Dacheng Tao Liangpei Zhang GAN 24 15 0 15 Dec 2021
Deep Active Contours Using Locally Controlled Distance Vector Flow Parastoo Akbarimoghaddam Atefeh Ziaei H. Azarnoush 25 5 0 18 May 2021
Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation Ali Hatamizadeh SSeg 21 3 0 23 Jun 2020
CNN-based Semantic Segmentation using Level Set Loss Youngeun Kim Seunghyeon Kim Taekyung Kim Changick Kim SSeg 16 56 0 02 Oct 2019
End-to-End Deep Convolutional Active Contours for Image Segmentation Ali Hatamizadeh Debleena Sengupta Demetri Terzopoulos 6 22 0 29 Sep 2019
MoBiNet: A Mobile Binary Network for Image Classification Hai T. Phan Dang T. Huynh Yihui He Marios Savvides Zhiqiang Shen MQ 16 48 0 29 Jul 2019