53 citations · 151 across the 8 of their papers we have counts for
8 papers
Unsupervised Domain Adaptation for Semantic Segmentation using One-shot Image-to-Image Translation via Latent Representation Mixing
Sarmad F. Ismael, Koray Kayabol, Erchan Aptoula
Domain adaptation is one of the prominent strategies for handling both domain shift, that is widely encountered in large-scale land use/land cover map calculation, and the scarcity…
SOMPT22: A Surveillance Oriented Multi-Pedestrian Tracking Dataset
Fatih Emre Simsek, Cevahir Cigla, Koray Kayabol
Multi-object tracking (MOT) has been dominated by the use of track by detection approaches due to the success of convolutional neural networks (CNNs) on detection in the last decad…
Unsupervised Pixel-wise Hyperspectral Anomaly Detection via Autoencoding Adversarial Networks
Sertac Arisoy, Nasser M. Nasrabadi, Koray Kayabol
We propose a completely unsupervised pixel-wise anomaly detection method for hyperspectral images. The proposed method consists of three steps called data preparation, reconstructi…
GAN-based Hyperspectral Anomaly Detection
Sertac Arisoy, Nasser M. Nasrabadi, Koray Kayabol
In this paper, we propose a generative adversarial network (GAN)-based hyperspectral anomaly detection algorithm. In the proposed algorithm, we train a GAN model to generate a synt…
A Bayesian technique for the detection of point sources in CMB maps
F. Argueso, E. Salerno, D. Herranz +3
The detection and flux estimation of point sources in cosmic microwave background (CMB) maps is a very important task in order to clean the maps and also to obtain relevant astroph…
Joint Bayesian separation and restoration of CMB from convolutional mixtures
K. Kayabol, J. L. Sanz, D. Herranz +2
We propose a Bayesian approach to joint source separation and restoration for astrophysical diffuse sources. We constitute a prior statistical model for the source images by using…
Adaptive Langevin Sampler for Separation of t-Distribution Modelled Astrophysical Maps
K. Kayabol, E. E. Kuruoglu, J. L. Sanz +3
We propose to model the image differentials of astrophysical source maps by Student's t-distribution and to use them in the Bayesian source separation method as priors. We introduc…
Correlated Component Analysis for diffuse component separation with error estimation on simulated Planck polarization data
S. Ricciardi, A. Bonaldi, P. Natoli +6
We present a data analysis pipeline for CMB polarization experiments, running from multi-frequency maps to the power spectra. We focus mainly on component separation and, for the f…