Ozgur Yilmaz

Ozgur Yilmaz

PhD

About

23
Publications
15,443
Reads
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324
Citations
Additional affiliations
November 2011 - September 2013
ASELSAN Inc.
Position
  • Researcher
November 2010 - October 2011
Bilkent University
Position
  • PostDoc Position
January 2008 - July 2008
Middle East Technical University
Position
  • Professor

Publications

Publications (23)
Article
Full-text available
Multi-view queries on a multi-view product image database with bag-of-visual words (BoWs) have been shown to improve the average precision significantly compared to traditional single view queries on single view databases. In this paper, we investigate the performance of deep convolutional neural networks (ConvNets) on multi-view product image sear...
Conference Paper
In this paper, we are analyzing how much computation and distributedness of representation is needed to solve sequence-learning tasks which are essential for many artificial intelligence applications. We propose a novel minimal architecture based on cellular automata. The states of the cells are used as the reservoir of activities as in Echo State...
Conference Paper
In today's technology, the popularity of the robotic systems is getting increased due to the fact that they facilitate Daily life and that they are becoming more functionality. In line with it, the robots that are cheap and easy to obtain are getting crucial. In the current study, a robot was created using materials cheap and easy to provide. After...
Article
Full-text available
In this study, we propose a simple yet very effective method for extracting color information through binary feature description framework. Our method expands the dimension of binary comparisons into RGB and YCbCr spaces, showing more than 100% matching improve ment compared to non-color binary descriptors for a wide range of hard-to-match cases. T...
Conference Paper
Full-text available
In this paper, we introduce a framework of reservoir computing that is capable of both connectionist machine intelligence and symbolic computation. Cellular automaton is used as the reservoir of dynamical systems. A cellular automaton is a very sparsely connected network with logical nodes and nonlinear/logical connection functions, hence the propo...
Article
Full-text available
This letter introduces a novel framework of reservoir computing that is capable of both connectionist machine intelligence and symbolic computation. A cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells, and nonlinear computation is performed on the input via a...
Article
Full-text available
Recurrent neural networks are powerful tools for handling incomplete data problems in computer vision, thanks to their significant generative capabilities. However, the computational demand for these algorithms is too high to work in real time, without specialized hardware or software solutions. In this paper, we propose a framework for augmenting...
Article
Full-text available
We introduce a novel framework of reservoir computing, that is capable of both connectionist machine intelligence and symbolic computation. Cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells and nonlinear computation is performed on the input via application o...
Article
In this paper, we introduce a novel framework of cellular automata based computing that is capable of long short-term memory. Cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells and nonlinear computation is performed on the input via application of a rule in th...
Article
Full-text available
We introduce a novel framework of reservoir computing. Cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells and nonlinear computation is performed on the input via application of a rule in the automaton for a period of time. The evolution of the automaton create...
Article
Full-text available
Successful identification of specularities in an image can be crucial for an artificial vision system when extracting the semantic content of an image or while interacting with the environment. We developed an algorithm that relies on scale and rotation invariant feature extraction techniques and uses motion cues to detect and localize specular sur...
Conference Paper
Full-text available
Robust and accurate 3D reconstruction of the scene is essential for many robotic and computer vision applications. We are proposing a system solution that can accurately reconstruct the scene both indoor and outdoor, in real-time. The system utilizes both active and passive visual sensors in conjunction with peripheral hardware for communication, a...
Article
Surface specularity distorts the optic flow generated by a moving object in a way that provides important cues for identifying surface material properties (Doerschner, Fleming et al., 2011). Here we show that specular flow can also affect the perceived rotation axis of objects. In three experiments, we investigate how three-dimensional shape and su...
Article
Full-text available
Trajectory perception is crucial in scene understanding and action. A variety of trajectory misperceptions have been reported in the literature. In this study, we quantify earlier observations that reported distortions in the perceived shape of bilinear trajectories and in the perceived positions of their deviation. Our results show that bilinear t...
Article
The world is a dynamic environment hence it is important for the visual system to be able to deploy attention on moving objects and attentively track them. Psychophysical experiments indicate that processes of both attentional enhancement and inhibition are spatially focused on the moving objects; however the mechanisms of these processes are unkno...
Article
Many critical perceptual judgments, from telling whether fruit is ripe to determining whether the ground is slippery, involve estimating the material properties of surfaces. Very little is known about how the brain recognizes materials, even though the problem is likely as important for survival as navigating or recognizing objects. Though previous...
Article
Full-text available
Multiple Object Tracking (MOT) experiments show that human observers can track over several seconds up to five moving targets among several moving distractors. We extended these studies by designing modified MOT experiments to investigate the spatio-temporal characteristics of human visuo-cognitive mechanisms for tracking and applied the findings a...
Article
Motion is known to distort visual space, producing illusory mislocalizations for flashed objects. Previously, it has been shown that when a stationary bar is flashed in the proximity of a moving stimulus, the position of the flashed bar appears to be shifted in the direction of nearby motion. A model consisting of predictive projections from the su...
Article
The perceived position of a stationary Gaussian window of a Gabor target shifts in the direction of motion of the Gabor's carrier stimulus, implying the presence of interactions between the specialized visual areas that encode form, position, and motion. The purpose of this study was to examine the temporal and spatial properties of this illusory m...

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