Papers › Neural Networks for Fashion Image Classification and Visual Search

Neural Networks for Fashion Image Classification and Visual Search

17 May 2020arXiv:2005.08170archive 2025-07-28

Fengzi Li, Shashi Kant, Shunichi Araki, Sumer Bangera, Swapna Samir Shukla

We discuss two potentially challenging problems faced by the ecommerce industry. One relates to the problem faced by sellers while uploading pictures of products on the platform for sale and the consequent manual tagging involved. It gives rise to misclassifications leading to its absence from search results. The other problem concerns with the potential bottleneck in placing orders when a customer may not know the right keywords but has a visual impression of an image. An image based search algorithm can unleash the true potential of ecommerce by enabling customers to click a picture of an object and search for similar products without the need for typing. In this paper, we explore machine learning algorithms which can help us solve both these problems.

PaperPDFCode

Code

swapnasamirshukla/BT5153-Term-Project officialmentioned in paper report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

Not run by Syntology. Nothing on this page verifies that the listed code works.

Tasks

ClassificationGeneral ClassificationImage Classificationimage-classification

Results from the paper archive 2025-07-28

No leaderboard rows for this paper in the archive.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections