Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Image captioning is a new difficult problem that has recently attracted a lot of attention. Currently, technologies that combine computer vision (CV), natural language processing (NLP), and machine learning techniques are used to complete the task of producing a brief description of an image in natural language. We described a model that creates a natural language description of an image in this work. Convolutional neural networks were combined to extract features, and recurrent neural networks were utilized to generate text from these features. When creating captions, we took the attention mechanism into consideration. Using the Flicker8k database, we assessed the model. The outcomes are encouraging and competitive.
"Image captioning using deep learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 4, page no.910 - 916, April-2023, Available :http://www.ijrti.org/papers/IJRTI2304149.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator