Search Results for author: Yuting Hu

Found 8 papers, 2 papers with code

Named Entity Recognition for Chinese biomedical patents

1 code implementation COLING 2020 Yuting Hu, Suzan Verberne

There is a large body of work on Biomedical Entity Recognition (Bio-NER) for English but there have only been a few attempts addressing NER for Chinese biomedical texts.

Named Entity Recognition NER

Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset

no code implementations16 Mar 2020 Yuting Hu, Zhiling Long, Anirudha Sundaresan, Motaz Alfarraj, Ghassan AlRegib, Sungmee Park, Sundaresan Jayaraman

We formulate the problem as a very fine-grained texture classification problem, and study how deep learning-based texture representation techniques can help tackle the task.

Material Recognition Object Recognition +2

Texture Classification using Block Intensity and Gradient Difference (BIGD) Descriptor

no code implementations4 Feb 2020 Yuting Hu, Zhen Wang, Ghassan AlRegib

In this paper, we present an efficient and distinctive local descriptor, namely block intensity and gradient difference (BIGD).

Classification General Classification +1

Multi-level Texture Encoding and Representation (MuLTER) based on Deep Neural Networks

1 code implementation23 May 2019 Yuting Hu, Zhiling Long, Ghassan AlRegib

In this paper, we propose a multi-level texture encoding and representation network (MuLTER) for texture-related applications.

Real-Time Steganalysis for Stream Media Based on Multi-channel Convolutional Sliding Windows

no code implementations4 Feb 2019 Zhongliang Yang, Hao Yang, Yuting Hu, Yongfeng Huang, Yu-Jin Zhang

To solve these two challenges, in this paper, combined with the sliding window detection algorithm and Convolution Neural Network we propose a real-time VoIP steganalysis method which based on multi-channel convolution sliding windows.

Window Detection

Twitter100k: A Real-world Dataset for Weakly Supervised Cross-Media Retrieval

no code implementations20 Mar 2017 Yuting Hu, Liang Zheng, Yi Yang, Yongfeng Huang

Second, texts in these datasets are written in well-organized language, leading to inconsistency with realistic applications.

Optical Character Recognition

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