The 2022 edition of the TRECVID benchmark has again been a fruitful participation for the RUCMM team.
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.
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)
The identification of protein-ligand interaction plays a key role in biochemical research and drug discovery.
Then, the fine-tuned model was used to select commercially available drugs against SARS-CoV-2 protein targets.
Each QA instance comprises a table of either kind, a natural language question, and a corresponding structured SQL query.
This paper aims to address the problem of detecting buildings from remote sensing images with very high resolution (VHR).
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.
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.
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.
The goal of AID is to advance the state-of-the-arts in scene classification of remote sensing images.
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.