Results 71 to 80 of about 4,895,571 (286)
Artificial molecular machines and motors—Design and control of nanoscale motion
FEBS Letters, EarlyView.Molecules are constantly moving because of thermal fluctuations, but random motion alone cannot be exploited to perform directional tasks. Artificial molecular machines use chemical, electrical, or light energy to bias this motion. Molecular shuttles, rotary motors, and supramolecular pumps illustrate how nanoscale movement can be controlled and ...
Leonardo Andreoni, Alberto Credi
wiley +1 more source
Visual Question Answering Using Semantic Information from Image Descriptions
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 In this work, we propose a deep neural architecture that uses an attention mechanism which utilizes region based image features, the natural language question asked, and semantic knowledge extracted from the regions of an image to produce open-ended ...
Tasmia Tasmia +2 more
doaj +1 more source
Selectively Answering Visual Questions
Findings of the Association for Computational Linguistics ACL 2024Recently, large multi-modal models (LMMs) have emerged with the capacity to perform vision tasks such as captioning and visual question answering (VQA) with unprecedented accuracy. Applications such as helping the blind or visually impaired have a critical need for precise answers.
Julian Eisenschlos +3 more
openaire +3 more sources
Visual Question Answering on Image Sets [PDF]
, 2020 Conference paper at ECCV ...
Ankan Bansal +2 more
openaire +3 more sources
Spatial biology in cancer epigenetics
Molecular Oncology, EarlyView.Spatial epigenomics combines molecular profiling with tissue architecture to reveal how gene regulation is organized within intact tissues. In cancer, these technologies uncover the mechanisms driving tumor heterogeneity and microenvironmental interactions, opening new opportunities for biomarker discovery and precision medicine.
Eva Crespo‐García, Manel Esteller
wiley +1 more source
LCC-DCU C-C question answering task at NTCIR-5 [PDF]
, 2005 This paper describes the work for our participation in the NTCIR-5 Chinese to Chinese Question Answering task. Our strategy is based on the “Retrieval plus Extraction” approach.
Jones, Gareth J.F., Wang, Bin
core +2 more sources
VISALOGY: Answering Visual Analogy Questions
CoRR, 2015 To appear in NIPS ...
Fereshteh Sadeghi +2 more
openaire +4 more sources
FEBS Open Bio, EarlyView.The cytoskeleton‐mediated transport of mitochondria via tunnelling nanotubes restores respiration, increases ATP production, rescues cells from apoptosis, activates the AKT/mTOR signalling pathway, promotes cell migration and invasiveness, contributes to cancer progression and treatment resistance.
Stanislava Martínková, Jan Trnka
wiley +1 more source
Big Data Mining and AnalyticsPrevious works employ the Large Language Model (LLM) like GPT-3 for knowledge-based Visual Question Answering (VQA). We argue that the inferential capacity of LLM can be enhanced through knowledge injection. Although methods that utilize knowledge graphs
Zhongjian Hu +4 more
doaj +1 more source
VQABQ: Visual Question Answering by Basic Questions
CoRR, 2017 Taking an image and question as the input of our method, it can output the text-based answer of the query question about the given image, so called Visual Question Answering (VQA). There are two main modules in our algorithm. Given a natural language question about an image, the first module takes the question as input and then outputs the basic ...
Jia-Hong Huang +2 more
openaire +3 more sources