Neural Twins Talk & Alternative Calculations | Awesome LLM Papers Add your paper to Awesome LLM Papers

Neural Twins Talk & Alternative Calculations

Zanyar Zohourianshahzadi, Jugal K. Kalita . Artificial Intelligence Review 2021 – 47 citations

[Paper]   Search on Google Scholar   Search on Semantic Scholar
Agentic Compositional Generalization Content Enrichment Image Text Integration Interactive Environments Interdisciplinary Approaches Multimodal Semantic Representation Neural Machine Translation Productivity Enhancement Question Answering Visual Contextualization

Inspired by how the human brain employs a higher number of neural pathways when describing a highly focused subject, we show that deep attentive models used for the main vision-language task of image captioning, could be extended to achieve better performance. Image captioning bridges a gap between computer vision and natural language processing. Automated image captioning is used as a tool to eliminate the need for human agent for creating descriptive captions for unseen images.Automated image captioning is challenging and yet interesting. One reason is that AI based systems capable of generating sentences that describe an input image could be used in a wide variety of tasks beyond generating captions for unseen images found on web or uploaded to social media. For example, in biology and medical sciences, these systems could provide researchers and physicians with a brief linguistic description of relevant images, potentially expediting their work.

Similar Work