b'Zhanyu Ma'

research

∙ 08/05/2023

LaDA: Latent Dialogue Action For Zero-shot Cross-lingual Neural Network Language Modeling

Cross-lingual adaptation has proven effective in spoken language underst...

0 Zhanyu Ma, et al. ∙

research

∙ 11/30/2022

Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification

The main challenge for fine-grained few-shot image classification is to ...

0 Jijie Wu, et al. ∙

research

∙ 07/15/2022

ScaleNet: Searching for the Model to Scale

Recently, community has paid increasing attention on model scaling and c...

0 Jiyang Xie, et al. ∙

research

∙ 06/02/2022

Multi-View Active Fine-Grained Recognition

As fine-grained visual classification (FGVC) being developed for decades...

0 Ruoyi Du, et al. ∙

research

∙ 06/01/2022

Learning Invariant Visual Representations for Compositional Zero-Shot Learning

Compositional Zero-Shot Learning (CZSL) aims to recognize novel composit...

0 Tian Zhang, et al. ∙

research

∙ 04/18/2022

Caption Feature Space Regularization for Audio Captioning

Audio captioning aims at describing the content of audio clips with huma...

0 Yiming Zhang, et al. ∙

research

∙ 01/20/2022

Domain Generalization via Frequency-based Feature Disentanglement and Interaction

Data out-of-distribution is a meta-challenge for all statistical learnin...

0 Jingye Wang, et al. ∙

research

∙ 12/06/2021

Clue Me In: Semi-Supervised FGVC with Out-of-Distribution Data

Despite great strides made on fine-grained visual classification (FGVC),...

0 Ruoyi Du, et al. ∙

research

∙ 12/06/2021

Making a Bird AI Expert Work for You and Me

As powerful as fine-grained visual classification (FGVC) is, responding ...

0 Dongliang Chang, et al. ∙

research

∙ 06/21/2021

Cross-layer Navigation Convolutional Neural Network for Fine-grained Visual Classification

Fine-grained visual classification (FGVC) aims to classify sub-classes o...

0 Chenyu Guo, et al. ∙

research

∙ 06/16/2021

Structured DropConnect for Uncertainty Inference in Image Classification

With the complexity of the network structure, uncertainty inference has ...

0 Wenqing Zheng, et al. ∙

research

∙ 06/16/2021

CMF: Cascaded Multi-model Fusion for Referring Image Segmentation

In this work, we address the task of referring image segmentation (RIS),...

0 Jianhua Yang, et al. ∙

research

∙ 06/07/2021

Channel DropBlock: An Improved Regularization Method for Fine-Grained Visual Classification

Classifying the sub-categories of an object from the same super-category...

0 Yifeng Ding, et al. ∙

research

∙ 05/17/2021

Deep Metric Learning for Few-Shot Image Classification: A Selective Review

Few-shot image classification is a challenging problem which aims to ach...

0 Xiaoxu Li, et al. ∙

research

∙ 04/01/2021

DF^2AM: Dual-level Feature Fusion and Affinity Modeling for RGB-Infrared Cross-modality Person Re-identification

RGB-infrared person re-identification is a challenging task due to the i...

0 Junhui Yin, et al. ∙

research

∙ 04/01/2021

Unsupervised Person Re-identification via Simultaneous Clustering and Consistency Learning

Unsupervised person re-identification (re-ID) has become an important to...

0 Junhui Yin, et al. ∙

research

∙ 03/11/2021

Duplex Contextual Relation Network for Polyp Segmentation

Polyp segmentation is of great importance in the early diagnosis and tre...

0 Zijin Yin, et al. ∙

research

∙ 01/31/2021

Fine-Grained Visual Classification via Simultaneously Learning of Multi-regional Multi-grained Features

Fine-grained visual classification is a challenging task that recognizes...

8 Dongliang Chang, et al. ∙

research

∙ 01/25/2021

ATRM: Attention-based Task-level Relation Module for GNN-based Few-shot Learning

Recently, graph neural networks (GNNs) have shown powerful ability to ha...

0 Yurong Guo, et al. ∙

research

∙ 01/24/2021

Grad-CAM guided channel-spatial attention module for fine-grained visual classification

Fine-grained visual classification (FGVC) is becoming an important resea...

0 Shuai Xu, et al. ∙

research

∙ 01/21/2021

Progressive Co-Attention Network for Fine-grained Visual Classification

Fine-grained visual classification aims to recognize images belonging to...

0 Tian Zhang, et al. ∙

research

∙ 12/21/2020

Knowledge Transfer Based Fine-grained Visual Classification

Fine-grained visual classification (FGVC) aims to distinguish the sub-cl...

0 Siqing Zhang, et al. ∙

research

∙ 12/15/2020

Dilated-Scale-Aware Attention ConvNet For Multi-Class Object Counting

Object counting aims to estimate the number of objects in images. The le...

0 Wei Xu, et al. ∙

research

∙ 11/29/2020

BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification

Few-shot learning for fine-grained image classification has gained recen...

3 Xiaoxu Li, et al. ∙

research

∙ 11/18/2020

Your "Labrador" is My "Dog": Fine-Grained, or Not

Whether what you see in Figure 1 is a "labrador" or a "dog", is the ques...

4 Dongliang Chang, et al. ∙

research

∙ 11/17/2020

DS-UI: Dual-Supervised Mixture of Gaussian Mixture Models for Uncertainty Inference

This paper proposes a dual-supervised uncertainty inference (DS-UI) fram...

0 Jiyang Xie, et al. ∙

research

∙ 11/02/2020

Actor and Action Modular Network for Text-based Video Segmentation

The actor and action semantic segmentation is a challenging problem that...

0 Jianhua Yang, et al. ∙

research

∙ 10/12/2020

CC-Loss: Channel Correlation Loss For Image Classification

The loss function is a key component in deep learning models. A commonly...

0 Zeyu Song, et al. ∙

research

∙ 10/11/2020

Advanced Dropout: A Model-free Methodology for Bayesian Dropout Optimization

Due to lack of data, overfitting ubiquitously exists in real-world appli...

0 Jiyang Xie, et al. ∙

research

∙ 09/14/2020

GINet: Graph Interaction Network for Scene Parsing

Recently, context reasoning using image regions beyond local convolution...

15 Tianyi Wu, et al. ∙

research

∙ 09/13/2020

SSKD: Self-Supervised Knowledge Distillation for Cross Domain Adaptive Person Re-Identification

Domain adaptive person re-identification (re-ID) is a challenging task d...

0 Junhui Yin, et al. ∙

research

∙ 06/27/2020

ReMarNet: Conjoint Relation and Margin Learning for Small-Sample Image Classification

Despite achieving state-of-the-art performance, deep learning methods ge...

0 Xiaoxu Li, et al. ∙

research

∙ 05/22/2020

A Concise Review of Recent Few-shot Meta-learning Methods

Few-shot meta-learning has been recently reviving with expectations to m...

0 Xiaoxu Li, et al. ∙

research

∙ 04/20/2020

OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax Layer

A deep neural network of multiple nonlinear layers forms a large functio...

0 Xiaoxu Li, et al. ∙

research

∙ 03/10/2020

Channel Attention with Embedding Gaussian Process: A Probabilistic Methodology

Channel attention mechanisms, as the key components of some modern convo...

0 Jiyang Xie, et al. ∙

research

∙ 03/09/2020

Dual-attention Guided Dropblock Module for Weakly Supervised Object Localization

In this paper, we propose a dual-attention guided dropblock module, and ...

0 Junhui Yin, et al. ∙

research

∙ 03/08/2020

Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches

Fine-grained visual classification (FGVC) is much more challenging than ...

6 Ruoyi Du, et al. ∙

research

∙ 03/08/2020

Mind the Gap: Enlarging the Domain Gap in Open Set Domain Adaptation

Unsupervised domain adaptation aims to leverage labeled data from a sour...

0 Dongliang Chang, et al. ∙

research

∙ 03/08/2020

Object-Oriented Video Captioning with Temporal Graph and Prior Knowledge Building

Traditional video captioning requests a holistic description of the vide...

0 Fangyi Zhu, et al. ∙

research

∙ 02/21/2020

Fine-Grained Instance-Level Sketch-Based Video Retrieval

Existing sketch-analysis work studies sketches depicting static objects ...

23 Peng Xu, et al. ∙

research

∙ 02/11/2020

The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification

Key for solving fine-grained image categorization is finding discriminat...

13 Dongliang Chang, et al. ∙

research

∙ 02/09/2020

Weakly Supervised Attention Pyramid Convolutional Neural Network for Fine-Grained Visual Classification

Classifying the sub-categories of an object from the same super-category...

22 Yifeng Ding, et al. ∙

research

∙ 11/10/2019

Semi-Heterogeneous Three-Way Joint Embedding Network for Sketch-Based Image Retrieval

Sketch-based image retrieval (SBIR) is a challenging task due to the lar...

10 Jianjun Lei, et al. ∙

research

∙ 07/31/2019

Competing Ratio Loss for Discriminative Multi-class Image Classification

The development of deep convolutional neural network architecture is cri...

2 Ke Zhang, et al. ∙

research

∙ 05/11/2019

Deep Zero-Shot Learning for Scene Sketch

We introduce a novel problem of scene sketch zero-shot learning (SSZSL),...

0 Yao Xie, et al. ∙

research

∙ 02/13/2019

On the Convergence of Extended Variational Inference for Non-Gaussian Statistical Models

Variational inference (VI) is a widely used framework in Bayesian estima...

10 Zhanyu Ma, et al. ∙

research

∙ 12/27/2018

Vehicular Edge Computing via Deep Reinforcement Learning

The smart vehicles construct Vehicle of Internet which can execute vario...

0 Qi Qi, et al. ∙

research

∙ 09/18/2018

Language Identification with Deep Bottleneck Features

In this paper we proposed an end-to-end short utterances speech language...

0 Zhanyu Ma, et al. ∙

research

∙ 08/02/2018

Dirichlet Mixture Model based VQ Performance Prediction for Line Spectral Frequency

In this paper, we continue our previous work on the Dirichlet mixture mo...

0 Zhanyu Ma, et al. ∙

research

∙ 08/02/2018

Impacts of Weather Conditions on District Heat System

Using artificial neural network for the prediction of heat demand has at...

0 Jiyang Xie, et al. ∙

Zhanyu Ma

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