ScholarIQanswers from OpenAlex
Multimodal Machine Learning Applications
TopicLeading institutions, researchers & key papers
Multimodal Machine Learning Applications is a topic indexed in ScholarIQ from OpenAlex.
What is known about Multimodal Machine Learning Applications?
ScholarIQrecord summary
This cluster of papers focuses on the development and improvement of visual question answering systems, image captioning techniques, and neural networks for understanding and generating descriptions of images and videos. The research involves semantic reasoning, multimodal fusion, scene graph generation, attention mechanisms, and deep learning approaches to bridge the gap between vision and language.
How many works does Multimodal Machine Learning Applications have?
ScholarIQindexed works
Multimodal Machine Learning Applications has 106 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.
What is the OpenAlex record for Multimodal Machine Learning Applications?
ScholarIQopenalex
The OpenAlex for Multimodal Machine Learning Applications is on the source record.
What are the most-cited papers on Multimodal Machine Learning Applications?
ScholarIQmost cited works
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A. Shamma, Michael S. Bernstein, Li Fei-Fei
Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy, Li Fei-Fei
A Comprehensive Survey of Deep Learning for Image Captioning
Md Zakir Hossain, Ferdous Sohel, Mohd Fairuz Shiratuddin, Hamid Laga
VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research
Xin Wang, Jiawei Wu, Junkun Chen, Lei Li, Yuan‐Fang Wang, William Yang Wang
GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition
Shih-Cheng Huang, Liyue Shen, Matthew P. Lungren, Serena Yeung
Where is Multimodal Machine Learning Applications research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
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How much of the research on Multimodal Machine Learning Applications is open access?
ScholarIQopen access share
27%OPEN ACCESS