no code implementations • 28 Nov 2022 • Xirong Li, Aozhu Chen, Ziyue Wang, Fan Hu, Kaibin Tian, Xinru Chen, Chengbo Dong
The 2022 edition of the TRECVID benchmark has again been a fruitful participation for the RUCMM team.
1 code implementation • 28 Oct 2022 • Yeming Gu, Hui Shu, Fan Hu
Binary code similarity detection (BCSD) is widely used in various binary analysis tasks such as vulnerability search, malware detection, clone detection, and patch analysis.
no code implementations • 9 Aug 2022 • Fan Hu, Dongqi Wang, Huazhen Huang, Yishen Hu, Peng Yin
Based on these findings, we utilized a monte carlo based reinforcement learning generative model to generate novel multi-property compounds with both in vitro and in vivo efficacy, thus bridging the gap between target-based and cell-based drug discovery.
1 code implementation • 30 Apr 2022 • Ziyue Wang, Aozhu Chen, Fan Hu, Xirong Li
We propose a learning based method for training a negation-aware video retrieval model.
1 code implementation • 3 Dec 2021 • Fan Hu, Aozhu Chen, Ziyue Wang, Fangming Zhou, Jianfeng Dong, Xirong Li
In this paper we revisit feature fusion, an old-fashioned topic, in the new context of text-to-video retrieval.
Ranked #1 on Ad-hoc video search on TRECVID-AVS20 (V3C1) (using extra training data)
no code implementations • 29 May 2021 • Fan Hu, Lei Wang, Yishen Hu, Dongqi Wang, Weijie Wang, Jianbing Jiang, Nan Li, Peng Yin
The identification of protein-ligand interaction plays a key role in biochemical research and drug discovery.
no code implementations • 2 Mar 2020 • Fan Hu, Jiaxin Jiang, Peng Yin
Then, the fine-tuned model was used to select commercially available drugs against SARS-CoV-2 protein targets.
no code implementations • 17 Mar 2019 • Bhavya Karki, Fan Hu, Nithin Haridas, Suhail Barot, Zihua Liu, Lucile Callebert, Matthias Grabmair, Anthony Tomasic
Each QA instance comprises a table of either kind, a natural language question, and a corresponding structured SQL query.
no code implementations • 4 Jun 2018 • Fan Hu, Gui-Song Xia, Wen Yang, Liangpei Zhang
Scene classification is a fundamental task in interpretation of remote sensing images, and has become an active research topic in remote sensing community due to its important role in a wide range of applications.
no code implementations • 4 Jun 2018 • Jin Huang, Gui-Song Xia, Fan Hu, Liangpei Zhang
This paper aims to address the problem of detecting buildings from remote sensing images with very high resolution (VHR).
no code implementations • 3 Jun 2018 • Pu Jin, Gui-Song Xia, Fan Hu, Qikai Lu, Liangpei Zhang
Aerial image scene classification is a fundamental problem for understanding high-resolution remote sensing images and has become an active research task in the field of remote sensing due to its important role in a wide range of applications.
no code implementations • 23 Jul 2017 • Xin-Yi Tong, Gui-Song Xia, Fan Hu, Yanfei Zhong, Mihai Datcu, Liangpei Zhang
Over the past two decades, a large amount of research on this task has been carried out, which mainly focuses on the following three core issues: feature extraction, similarity metric and relevance feedback.
1 code implementation • 18 Aug 2016 • Gui-Song Xia, Jingwen Hu, Fan Hu, Baoguang Shi, Xiang Bai, Yanfei Zhong, Liangpei Zhang
The goal of AID is to advance the state-of-the-arts in scene classification of remote sensing images.
no code implementations • 4 Feb 2015 • Jingwen Hu, Gui-Song Xia, Fan Hu, Liangpei Zhang
The experimental results on two commonly used datasets show that dense sampling has the best performance among all the strategies but with high spatial and computational complexity, random sampling gives better or comparable results than other sparse sampling methods, like the sophisticated multi-scale key-point operators and the saliency-based methods which are intensively studied and commonly used recently.