27 citations · 85 across the 19 of their papers we have counts for
5 papers · 1 filter
What is (missing or wrong) in the scene? A Hybrid Deep Boltzmann Machine For Contextualized Scene Modeling
İlker Bozcan, Yağmur Oymak, İdil Zeynep Alemdar +1
Scene models allow robots to reason about what is in the scene, what else should be in it, and what should not be in it. In this paper, we propose a hybrid Boltzmann Machine (BM) f…
CINet: A Learning Based Approach to Incremental Context Modeling in Robots
Fethiye Irmak Doğan, İlker Bozcan, Mehmet Çelik +1
There have been several attempts at modeling context in robots. However, either these attempts assume a fixed number of contexts or use a rule-based approach to determine when to i…
A Deep Incremental Boltzmann Machine for Modeling Context in Robots
Fethiye Irmak Doğan, Hande Çelikkanat, Sinan Kalkan
Context is an essential capability for robots that are to be as adaptive as possible in challenging environments. Although there are many context modeling efforts, they assume a fi…
Using Deep Networks for Drone Detection
Cemal Aker, Sinan Kalkan
Drone detection is the problem of finding the smallest rectangle that encloses the drone(s) in a video sequence. In this study, we propose a solution using an end-to-end object det…
A Large-scale Dataset and Benchmark for Similar Trademark Retrieval
Osman Tursun, Cemal Aker, Sinan Kalkan
Trademark retrieval (TR) has become an important yet challenging problem due to an ever increasing trend in trademark applications and infringement incidents. There have been many…