Search Results for author: Zhiwen Yu

Found 21 papers, 3 papers with code

AskMe: Joint Individual-level and Community-level Behavior Interaction for Question Recommendation

no code implementations11 Oct 2021 Nuo Li, Bin Guo, Yan Liu, Lina Yao, Jiaqi Liu, Zhiwen Yu

On the one hand, we model the rich correlations between the users' diverse behaviors (e. g., answer, follow, vote) to obtain the individual-level behavior interaction.

Community Question Answering

DeepExpress: Heterogeneous and Coupled Sequence Modeling for Express Delivery Prediction

no code implementations18 Aug 2021 Siyuan Ren, Bin Guo, Longbing Cao, Ke Li, Jiaqi Liu, Zhiwen Yu

To address these issues, we propose DeepExpress - a deep-learning based express delivery sequence prediction model, which extends the classic seq2seq framework to learning complex coupling between sequence and features.

TL-SDD: A Transfer Learning-Based Method for Surface Defect Detection with Few Samples

no code implementations16 Aug 2021 Jiahui Cheng, Bin Guo, Jiaqi Liu, Sicong Liu, Guangzhi Wu, Yueqi Sun, Zhiwen Yu

To solve the imbalanced distribution problem, in this paper we propose TL-SDD: a novel Transfer Learning-based method for Surface Defect Detection.

Defect Detection Transfer Learning

Mask-Embedded Discriminator With Region-Based Semantic Regularization for Semi-Supervised Class-Conditional Image Synthesis

no code implementations CVPR 2021 Yi Liu, Xiaoyang Huo, Tianyi Chen, Xiangping Zeng, Si Wu, Zhiwen Yu, Hau-San Wong

Semi-supervised generative learning (SSGL) makes use of unlabeled data to achieve a trade-off between the data collection/annotation effort and generation performance, when adequate labeled data are not available.

Image Generation

AdaSpring: Context-adaptive and Runtime-evolutionary Deep Model Compression for Mobile Applications

no code implementations28 Jan 2021 Sicong Liu, Bin Guo, Ke Ma, Zhiwen Yu, Junzhao Du

There are many deep learning (e. g., DNN) powered mobile and wearable applications today continuously and unobtrusively sensing the ambient surroundings to enhance all aspects of human lives.

Model Compression

Object Tracking by Least Spatiotemporal Searches

no code implementations18 Jul 2020 Zhiyong Yu, Lei Han, Chao Chen, Wenzhong Guo, Zhiwen Yu

This paper proposes a strategy named IHMs (Intermediate Searching at Heuristic Moments): each step we figure out which moment is the best to search according to a heuristic indicator, then at that moment search locations one by one in descending order of predicted appearing probabilities, until a search hits; iterate this step until we get the object's current location.

Object Tracking

Towards information-rich, logical text generation with knowledge-enhanced neural models

no code implementations2 Mar 2020 Hao Wang, Bin Guo, Wei Wu, Zhiwen Yu

Text generation system has made massive promising progress contributed by deep learning techniques and has been widely applied in our life.

Text Generation

Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities

no code implementations21 Jan 2020 Kaixuan Chen, Dalin Zhang, Lina Yao, Bin Guo, Zhiwen Yu, Yunhao Liu

In this study, we present a survey of the state-of-the-art deep learning methods for sensor-based human activity recognition.

Activity Recognition

The Future of Misinformation Detection: New Perspectives and Trends

no code implementations9 Sep 2019 Bin Guo, Yasan Ding, Lina Yao, Yunji Liang, Zhiwen Yu

We first give a brief review of the literature history of MID, based on which we present several new research challenges and techniques of it, including early detection, detection by multimodal data fusion, and explanatory detection.

Misinformation

Conditional Text Generation for Harmonious Human-Machine Interaction

no code implementations8 Sep 2019 Bin Guo, Hao Wang, Yasan Ding, Wei Wu, Shaoyang Hao, Yueqi Sun, Zhiwen Yu

In recent years, with the development of deep learning, text generation technology has undergone great changes and provided many kinds of services for human beings, such as restaurant reservation and daily communication.

Conditional Text Generation

Multi-agent Attentional Activity Recognition

no code implementations22 May 2019 Kaixuan Chen, Lina Yao, Dalin Zhang, Bin Guo, Zhiwen Yu

And the multiple agents in the proposed model represent activities with collective motions across body parts by independently selecting modalities associated with single motions.

Activity Recognition

AI-Powered Text Generation for Harmonious Human-Machine Interaction: Current State and Future Directions

no code implementations1 May 2019 Qiuyun Zhang, Bin Guo, Hao Wang, Yunji Liang, Shaoyang Hao, Zhiwen Yu

In the last two decades, the landscape of text generation has undergone tremendous changes and is being reshaped by the success of deep learning.

Text Generation

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.

Metabolize Neural Network

no code implementations4 Sep 2018 Dan Dai, Zhiwen Yu, Yang Hu, Wenming Cao, Mingnan Luo

It is self-evident that the significance of metabolize neuronal network(MetaNet) in model construction.

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.

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.

CityTransfer: Transferring Inter- and Intra-City Knowledge for Chain Store Site Recommendation based on Multi-Source Urban Data

1 code implementation https://dl.acm.org/doi/10.1145/3161411 2018 Bin Guo, Jing Li, Vincent W. Zheng, Zhu Wang, Zhiwen Yu

To solve the cold-start problem, we propose CityTransfer, which transfers chain store knowledge from semantically-relevant domains (e. g., other cities with rich knowledge, similar chain enterprises in the target city) for chain store placement recommendation in a new city.

Collaborative Filtering Transfer Learning

Cannot find the paper you are looking for? You can Submit a new open access paper.