• Ranjani K
• Gokul V
• Sridevi R
• Mrs.M.Poonkodi

In this current world, the need for tagging an image has been increased. Social media plays a major role in people’s lives, which created the need for image tagging. People’s phones and systems are dumped with images without proper tags and it is hard to find an image. Previous image tagging models have a limitation such that it could only tag personal images and the web images will not be tagged. Image tagging is based on labelling or tagging images. The technology enables the automatic assignment of tags or relevant keywords to a vast collection of images using Transfer learning. The features extracted from the image using CNN are fed into an artificial neural network. The tags predicted by neural network is mapped to word vector model, which are then added along with the Zero shot tagging that has the ability to assign tags to images outside its own training class examples. We experiment with a large scale MLflickr-25k dataset.

ImageTagging,Transferlearning,Convolutional neural network.

"Image Tagging", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.111-114, May-2020, Available :http://www.jetir.org/papers/JETIRDV06025.pdf

"Image Tagging", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 5, page no. pp111-114, May-2020, Available at : http://www.jetir.org/papers/JETIRDV06025.pdf