4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CV2025★ 1 cited
Benchmarking Image Embeddings for E-Commerce: Evaluating Off-the Shelf Foundation Models, Fine-Tuning Strategies and Practical Trade-offs
Urszula Czerwinska, Cenk Bircanoglu, Jeremy Chamoux
We benchmark foundation models image embeddings for classification and retrieval in e-Commerce, evaluating their suitability for real-world applications. Our study spans embeddings…
cs.CV2022★ 4 cited
ISIM: Iterative Self-Improved Model for Weakly Supervised Segmentation
Cenk Bircanoglu, Nafiz Arica
Weakly Supervised Semantic Segmentation (WSSS) is a challenging task aiming to learn the segmentation labels from class-level labels. In the literature, exploiting the information…
cs.CV2020
A Comparative Study on Effects of Original and Pseudo Labels for Weakly Supervised Learning for Car Localization Problem
Cenk Bircanoglu
In this study, the effects of different class labels created as a result of multiple conceptual meanings on localization using Weakly Supervised Learning presented on Car Dataset.…