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researcher

Anika Tabassum Sejuty

2 papers hereh-index 358 citations5 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.IR1

identity via Semantic Scholar / OpenAlex

most citedA Survey of Recommender System Techniques and the Ecommerce Domain

3 citations · 5 across the 2 of their papers we have counts for

collaborators

2 papers

cs.AI2023★ 2 cited

Generative Adversarial Networks for Data Augmentation

Angona Biswas, MD Abdullah Al Nasim, Al Imran +4

One way to expand the available dataset for training AI models in the medical field is through the use of Generative Adversarial Networks (GANs) for data augmentation. GANs work by…

cs.IR2022★ 3 cited

A Survey of Recommender System Techniques and the Ecommerce Domain

Imran Hossain, Md Aminul Haque Palash, Anika Tabassum Sejuty +6

In this big data era, it is hard for the current generation to find the right data from the huge amount of data contained within online platforms. In such a situation, there is a n…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.