Search Results for author: Fan Hu

Found 14 papers, 4 papers with code

UniASM: Binary Code Similarity Detection without Fine-tuning

1 code implementation28 Oct 2022 Yeming Gu, Hui Shu, Fan Hu

The experimental results show that UniASM outperforms state-of-the-art (SOTA) approaches on the evaluation dataset.

Clone Detection Malware Detection

Bridging the gap between target-based and cell-based drug discovery with a graph generative multi-task model

no code implementations9 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.

Drug Discovery

Learn to Understand Negation in Video Retrieval

1 code implementation30 Apr 2022 Ziyue Wang, Aozhu Chen, Fan Hu, Xirong Li

We propose a learning based method for training a negation-aware video retrieval model.

Natural Language Queries Retrieval +2

Lightweight Attentional Feature Fusion: A New Baseline for Text-to-Video Retrieval

1 code implementation3 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)

Ad-hoc video search Retrieval +2

Prediction of Potential Commercially Available Inhibitors against SARS-CoV-2 by Multi-Task Deep Learning Model

no code implementations2 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.

Molecular Docking

Question Answering via Web Extracted Tables and Pipelined Models

no code implementations17 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.

Question Answering Retrieval

Accurate Building Detection in VHR Remote Sensing Images using Geometric Saliency

no code implementations4 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).

Recent advances and opportunities in scene classification of aerial images with deep models

no code implementations4 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.

Classification General Classification +1

AID++: An Updated Version of AID on Scene Classification

no code implementations3 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.

Aerial Scene Classification Classification +2

Exploiting Deep Features for Remote Sensing Image Retrieval: A Systematic Investigation

no code implementations23 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.

Image Retrieval Retrieval

Dense v.s. Sparse: A Comparative Study of Sampling Analysis in Scene Classification of High-Resolution Remote Sensing Imagery

no code implementations4 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.

Classification General Classification +2

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