Orhun Buğra Baran

Department of Computer Engineering
Scopus Author ID
Web of Science Researcher ID
Semantics-driven attentive few-shot learning over clean and noisy samples
Baran, Orhun Buğra; Cinbiş, Ramazan Gökberk (2022-11-01)
Over the last couple of years, few-shot learning (FSL) has attracted significant attention towards minimiz-ing the dependency on labeled training examples. An inherent difficulty in FSL is handling ambiguities resulting fr...
Closed-form sample probing for learning generative models in Zero-shot Learning
Çetin, Samet; Baran, Orhun Buğra; Cinbiş, Ramazan Gökberk (2022-04-25)
Generative model based approaches have led to significant advances in zero-shot learning (ZSL) over the past few years. These approaches typically aim to learn a conditional generator that synthesizes training samples of c...
MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation
Amac, Mustafa Sercan; Sencan, Ahmet; Baran, Orhun Buğra; Ikizler-Cinbis, Nazli; Cinbiş, Ramazan Gökberk (2022-01-01)
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 the few-shot setting reduces this cost for ...
Citation Formats