Search Results for author: Guihua Wen

Found 16 papers, 2 papers with code

Unsupervised Domain Adaptation via Deep Hierarchical Optimal Transport

no code implementations21 Nov 2022 Yingxue Xu, Guihua Wen, Yang Hu, Pei Yang

In this paper, we propose a Deep Hierarchical Optimal Transport method (DeepHOT) for unsupervised domain adaptation.

Image Classification Unsupervised Domain Adaptation

Duck swarm algorithm: a novel swarm intelligence algorithm

no code implementations27 Dec 2021 Mengjian Zhang, Guihua Wen, Jing Yang

A swarm intelligence-based optimization algorithm, named Duck Swarm Algorithm (DSA), is proposed in this paper.

Speech-T: Transducer for Text to Speech and Beyond

no code implementations NeurIPS 2021 Jiawei Chen, Xu Tan, Yichong Leng, Jin Xu, Guihua Wen, Tao Qin, Tie-Yan Liu

Experiments on LJSpeech datasets demonstrate that Speech-T 1) is more robust than the attention based autoregressive TTS model due to its inherent monotonic alignments between text and speech; 2) naturally supports streaming TTS with good voice quality; and 3) enjoys the benefit of joint modeling TTS and ASR in a single network.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Inner-Imaging Networks: Put Lenses into Convolutional Structure

1 code implementation22 Apr 2019 Yang Hu, Guihua Wen, Mingnan Luo, Dan Dai, Wenming Cao, Zhiwen Yu, Wendy Hall

To deal with these problems, a novel Inner-Imaging architecture is proposed in this paper, which allows relationships between channels to meet the above requirement.

Stochastic Region Pooling: Make Attention More Expressive

no code implementations22 Apr 2019 Mingnan Luo, Guihua Wen, Yang Hu, Dan Dai, Yingxue Xu

Global Average Pooling (GAP) is used by default on the channel-wise attention mechanism to extract channel descriptors.

Chinese Herbal Recognition based on Competitive Attentional Fusion of Multi-hierarchies Pyramid Features

no code implementations23 Dec 2018 Yingxue Xu, Guihua Wen, Yang Hu, Mingnan Luo, Dan Dai, Yishan Zhuang

According to the characteristics of herbal images, we proposed the competitive attentional fusion pyramid networks to model the features of herbal image, which mdoels the relationship of feature maps from different levels, and re-weights multi-level channels with channel-wise attention mechanism.

Convolutional herbal prescription building method from multi-scale facial features

no code implementations17 Dec 2018 Huiqiang Liao, Guihua Wen, Yang Hu, Changjun Wang

In order to mine features from different granularities of faces, we design a multi-scale convolutional neural network based on three-grained face, which mines the patient's face information from the organs, local regions, and the entire face.

Competitive Inner-Imaging Squeeze and Excitation for Residual Network

1 code implementation24 Jul 2018 Yang Hu, Guihua Wen, Mingnan Luo, Dan Dai, Jiajiong Ma, Zhiwen Yu

In this work, we propose a competitive squeeze-excitation (SE) mechanism for the residual network.

Tongue image constitution recognition based on Complexity Perception method

no code implementations1 Mar 2018 Jiajiong Ma, Guihua Wen, Yang Hu, Tianyuan Chang, Haibin Zeng, Lijun Jiang, Jianzeng Qin

To evaluate the performance of our proposed method, we conduct experiments on three sizes of tongue datasets, in which deep convolutional neural network method and traditional digital image analysis method are respectively applied to extract features for tongue images.

Classification General Classification

Automatic construction of Chinese herbal prescription from tongue image via CNNs and auxiliary latent therapy topics

no code implementations23 Jan 2018 Yang Hu, Guihua Wen, Huiqiang Liao, Changjun Wang, Dan Dai, Zhiwen Yu

In order to adapt to the tongue image in a variety of photographic environments and construct herbal prescriptions, a neural network framework for prescription construction is designed.

Conceptualization Topic Modeling

no code implementations7 Apr 2017 Yi-Kun Tang, Xian-Ling Mao, He-Yan Huang, Guihua Wen

Recently, topic modeling has been widely used to discover the abstract topics in text corpora.

Topic Models

Supervised Deep Hashing for Hierarchical Labeled Data

no code implementations7 Apr 2017 Dan Wang, He-Yan Huang, Chi Lu, Bo-Si Feng, Liqiang Nie, Guihua Wen, Xian-Ling Mao

Specifically, we define a novel similarity formula for hierarchical labeled data by weighting each layer, and design a deep convolutional neural network to obtain a hash code for each data point.

Deep Hashing Image Retrieval

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