activity
20172022
most citedFine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery

91 citations · 249 across the 8 of their papers we have counts for

collaborators

13 papers

cs.CV2021

MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation

Mustafa Sercan Amac, Ahmet Sencan, Orhun Bugra Baran +2

Just like other few-shot learning problems, few-shot segmentation aims to minimize the need for manual annotation, which is particularly costly in segmentation tasks. Even though t…

cs.CV202120 cited

Weakly Supervised Instance Attention for Multisource Fine-Grained Object Recognition with an Application to Tree Species Classification

Bulut Aygunes, Ramazan Gokberk Cinbis, Selim Aksoy

Multisource image analysis that leverages complementary spectral, spatial, and structural information benefits fine-grained object recognition that aims to classify an object into…

cs.CV2020

Red Carpet to Fight Club: Partially-supervised Domain Transfer for Face Recognition in Violent Videos

Yunus Can Bilge, Mehmet Kerim Yucel, Ramazan Gokberk Cinbis +2

In many real-world problems, there is typically a large discrepancy between the characteristics of data used in training versus deployment. A prime example is the analysis of aggre…

cs.CV2020

A Deep Dive into Adversarial Robustness in Zero-Shot Learning

Mehmet Kerim Yucel, Ramazan Gokberk Cinbis, Pinar Duygulu

Machine learning (ML) systems have introduced significant advances in various fields, due to the introduction of highly complex models. Despite their success, it has been shown mul…

cs.LG2019

Key Protected Classification for Collaborative Learning

Mert Bülent Sarıyıldız, Ramazan Gökberk Cinbiş, Erman Ayday

Large-scale datasets play a fundamental role in training deep learning models. However, dataset collection is difficult in domains that involve sensitive information. Collaborative…

cs.CV2019

Image Captioning with Unseen Objects

Berkan Demirel, Ramazan Gokberk Cinbis, Nazli Ikizler-Cinbis

Image caption generation is a long standing and challenging problem at the intersection of computer vision and natural language processing. A number of recently proposed approaches…