1 citations · 2 across the 3 of their papers we have counts for
3 papers
eess.IV2019★ 1 cited
Deep Mouse: An End-to-end Auto-context Refinement Framework for Brain Ventricle and Body Segmentation in Embryonic Mice Ultrasound Volumes
Tongda Xu, Ziming Qiu, William Das +8
High-frequency ultrasound (HFU) is well suited for imaging embryonic mice due to its noninvasive and real-time characteristics. However, manual segmentation of the brain ventricles…
eess.IV2019★ 1 cited
Automatic Mouse Embryo Brain Ventricle & Body Segmentation and Mutant Classification From Ultrasound Data Using Deep Learning
Ziming Qiu, Nitin Nair, Jack Langerman +5
High-frequency ultrasound (HFU) is well suited for imaging embryonic mice in vivo because it is non-invasive and real-time. Manual segmentation of the brain ventricles (BVs) and wh…
cs.CL2019
Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion
Jonathan Mamou, Oren Pereg, Moshe Wasserblat +1
In this paper, we present a novel algorithm that combines multi-context term embeddings using a neural classifier and we test this approach on the use case of corpus-based term set…