Search Results for author: Hongzhi Xu

Found 19 papers, 3 papers with code

Real-time landmark detection for precise endoscopic submucosal dissection via shape-aware relation network

1 code implementation8 Nov 2021 Jiacheng Wang, Yueming Jin, Shuntian Cai, Hongzhi Xu, Pheng-Ann Heng, Jing Qin, Liansheng Wang

Compared with existing solutions, which either neglect geometric relationships among targeting objects or capture the relationships by using complicated aggregation schemes, the proposed network is capable of achieving satisfactory accuracy while maintaining real-time performance by taking full advantage of the spatial relations among landmarks.

Multi-Task Learning

Modeling Morphological Typology for Unsupervised Learning of Language Morphology

no code implementations ACL 2020 Hongzhi Xu, Jordan Kodner, Mitchell Marcus, Charles Yang

This paper describes a language-independent model for fully unsupervised morphological analysis that exploits a universal framework leveraging morphological typology.

Morphological Analysis

Morphological Segmentation for Low Resource Languages

no code implementations LREC 2020 Justin Mott, Ann Bies, Stephanie Strassel, Jordan Kodner, Caitlin Richter, Hongzhi Xu, Mitchell Marcus

This paper describes a new morphology resource created by Linguistic Data Consortium and the University of Pennsylvania for the DARPA LORELEI Program.

Unsupervised Morphology Learning with Statistical Paradigms

1 code implementation COLING 2018 Hongzhi Xu, Mitchell Marcus, Charles Yang, Lyle Ungar

This paper describes an unsupervised model for morphological segmentation that exploits the notion of paradigms, which are sets of morphological categories (e. g., suffixes) that can be applied to a homogeneous set of words (e. g., nouns or verbs).

Information Retrieval Text Generation

Database of Mandarin Neighborhood Statistics

1 code implementation LREC 2016 Karl Neergaard, Hongzhi Xu, Chu-Ren Huang

In the design of controlled experiments with language stimuli, researchers from psycholinguistic, neurolinguistic, and related fields, require language resources that isolate variables known to affect language processing.


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