Search Results for author: wenbin liu

Found 10 papers, 0 papers with code

ISTIC’s Triangular Machine Translation System for WMT2021

no code implementations WMT (EMNLP) 2021 Hangcheng Guo, wenbin liu, yanqing he, Tian Lan, Hongjiao Xu, zhenfeng wu, you pan

This paper describes the ISTIC’s submission to the Triangular Machine Translation Task of Russian-to-Chinese machine translation for WMT’ 2021.

Machine Translation Translation

From Incomplete Coarse-Grained to Complete Fine-Grained: A Two-Stage Framework for Spatiotemporal Data Reconstruction

no code implementations5 Oct 2024 Ziyu Sun, Haoyang Su, En Wang, Funing Yang, Yongjian Yang, wenbin liu

With the rapid development of various sensing devices, spatiotemporal data is becoming increasingly important nowadays.

Denoising

End-to-end Multi-source Visual Prompt Tuning for Survival Analysis in Whole Slide Images

no code implementations5 Sep 2024 Zhongwei Qiu, Hanqing Chao, wenbin liu, Yixuan Shen, Le Lu, Ke Yan, Dakai Jin, Yun Bian, Hui Jiang

Survival analysis using pathology images poses a considerable challenge, as it requires the localization of relevant information from the multitude of tiles within whole slide images (WSIs).

Decoder Survival Analysis +3

Toward Time-Continuous Data Inference in Sparse Urban CrowdSensing

no code implementations27 Aug 2024 Ziyu Sun, Haoyang Su, Hanqi Sun, En Wang, wenbin liu

Mobile Crowd Sensing (MCS) is a promising paradigm that leverages mobile users and their smart portable devices to perform various real-world tasks.

SkinCAP: A Multi-modal Dermatology Dataset Annotated with Rich Medical Captions

no code implementations28 May 2024 Juexiao Zhou, Liyuan Sun, Yan Xu, wenbin liu, Shawn Afvari, Zhongyi Han, Jiaoyan Song, Yongzhi Ji, Xiaonan He, Xin Gao

To address this gap and provide a meticulously annotated dermatology dataset with comprehensive natural language descriptions, we introduce SkinCAP: a multi-modal dermatology dataset annotated with rich medical captions.

ISTIC's Neural Machine Translation System for IWSLT'2020

no code implementations WS 2020 jiaze wei, wenbin liu, zhenfeng wu, you pan, yanqing he

This paper introduces technical details of machine translation system of Institute of Scientific and Technical Information of China (ISTIC) for the 17th International Conference on Spoken Language Translation (IWSLT 2020).

Machine Translation Translation

Cell Selection with Deep Reinforcement Learning in Sparse Mobile Crowdsensing

no code implementations19 Apr 2018 Leye Wang, wenbin liu, Daqing Zhang, Yasha Wang, En Wang, Yongjian Yang

Since the sensed data from different cells (sub-areas) of the target sensing area will probably lead to diverse levels of inference data quality, cell selection (i. e., choose which cells of the target area to collect sensed data from participants) is a critical issue that will impact the total amount of data that requires to be collected (i. e., data collection costs) for ensuring a certain level of quality.

Deep Reinforcement Learning reinforcement-learning +2

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