75 citations · 342 across the 18 of their papers we have counts for
19 papers
Through the Gaps: Uncovering Tactical Line-Breaking Passes with Clustering
Oktay Karakuş, Hasan Arkadaş
Line-breaking passes (LBPs) are crucial tactical actions in football, allowing teams to penetrate defensive lines and access high-value spaces. In this study, we present an unsuper…
Core-Set Selection for Data-efficient Land Cover Segmentation
Keiller Nogueira, Akram Zaytar, Wanli Ma +9
The increasing accessibility of remotely sensed data and their potential to support large-scale decision-making have driven the development of deep learning models for many Earth O…
TopoFormer: Integrating Transformers and ConvLSTMs for Coastal Topography Prediction
Santosh Munian, Oktay Karakuş, William Russell +1
This paper presents \textit{TopoFormer}, a novel hybrid deep learning architecture that integrates transformer-based encoders with convolutional long short-term memory (ConvLSTM) l…
A Multimodal Approach for Fluid Overload Prediction: Integrating Lung Ultrasound and Clinical Data
Tianqi Yang, Nantheera Anantrasirichai, Oktay Karakuş +2
Managing fluid balance in dialysis patients is crucial, as improper management can lead to severe complications. In this paper, we propose a multimodal approach that integrates vis…
CPSNet: Physics-Inspired Label-Free Deep Unfolding for Lung Ultrasound B-Line Detection
Tianqi Yang, Oktay Karakuş, Nantheera Anantrasirichai +2
In this paper, we propose CPSNet, a label-free deep unfolding framework for lung ultrasound image analysis. CPSNet unfolds a Cauchy proximal splitting algorithm into a forward-back…
Bayes-xG: Player and Position Correction on Expected Goals (xG) using Bayesian Hierarchical Approach
Alexander Scholtes, Oktay Karakuş
This study employs Bayesian methodologies to explore the influence of player or positional factors in predicting the probability of a shot resulting in a goal, measured by the expe…
DUBLINE: A Deep Unfolding Network for B-line Detection in Lung Ultrasound Images
Tianqi Yang, Nantheera Anantrasirichai, Oktay Karakuş +3
In the context of lung ultrasound, the detection of B-lines, which are indicative of interstitial lung disease and pulmonary edema, plays a pivotal role in clinical diagnosis. Curr…
Robust Kalman Filters Based on the Sub-Gaussian -stable Distribution
Pengcheng Hao, Oktay Karakuş, Alin Achim
Motivated by filtering tasks under a linear system with non-Gaussian heavy-tailed noise, various robust Kalman filters (RKFs) based on different heavy-tailed distributions have bee…
Sentiment Analysis for Measuring Hope and Fear from Reddit Posts During the 2022 Russo-Ukrainian Conflict
Alessio Guerra, Oktay Karakuş
This paper proposes a novel lexicon-based unsupervised sentimental analysis method to measure the and for the 2022 Ukrainian-Russian Conflict.…
A Machine Learning Approach for Player and Position Adjusted Expected Goals in Football (Soccer)
James H. Hewitt, Oktay Karakuş
Football is a very result-driven industry, with goals being rarer than in most sports, so having further parameters to judge the performance of teams and individuals is key. Expect…
Exploiting the Dual-Tree Complex Wavelet Transform for Ship Wake Detection in SAR Imagery
Wanli Ma, Alin Achim, Oktay Karakuş
In this paper, we analyse synthetic aperture radar (SAR) images of the sea surface using an inverse problem formulation whereby Radon domain information is enhanced in order to acc…
A Simulation Study to Evaluate the Performance of the Cauchy Proximal Operator in Despeckling SAR Images of the Sea Surface
Oktay Karakuş, Igor Rizaev, Alin Achim
The analysis of ocean surface is widely performed using synthetic aperture radar (SAR) imagery as it yields information for wide areas under challenging weather conditions, during…
On Solving SAR Imaging Inverse Problems Using Non-Convex Regularization with a Cauchy-based Penalty
Oktay Karakuş, Alin Achim
Synthetic aperture radar (SAR) imagery can provide useful information in a multitude of applications, including climate change, environmental monitoring, meteorology, high dimensio…
A Generalized Gaussian Extension to the Rician Distribution for SAR Image Modeling
Oktay Karakuş, Ercan E. Kuruoglu, Alin Achim
In this paper, we present a novel statistical model, (GG-Rician) distribution, for the characterization of synthetic aperture radar (SAR)…
Detection of Line Artefacts in Lung Ultrasound Images of COVID-19 Patients via Non-Convex Regularization
Oktay Karakuş, Nantheera Anantrasirichai, Amazigh Aguersif +3
In this paper, we present a novel method for line artefacts quantification in lung ultrasound (LUS) images of COVID-19 patients. We formulate this as a non-convex regularisation pr…
Convergence Guarantees for Non-Convex Optimisation with Cauchy-Based Penalties
Oktay Karakus, Perla Mayo, Alin Achim
In this paper, we propose a proximal splitting methodology with a non-convex penalty function based on the heavy-tailed Cauchy distribution. We first suggest a closed-form expressi…
Detection of Ship Wakes in SAR Imagery Using Cauchy Regularisation
Tianqi Yang, Oktay Karakuş, Alin Achim
Ship wake detection is of great importance in the characterisation of synthetic aperture radar (SAR) images of the ocean surface since wakes usually carry essential information abo…
Ship Wake Detection in SAR Images via Sparse Regularization
Oktay Karakuş, Igor Rizaev, Alin Achim
In order to analyse synthetic aperture radar (SAR) images of the sea surface, ship wake detection is essential for extracting information on the wake generating vessels. One possib…
Beyond trans-dimensional RJMCMC with a case study in impulsive data modeling
Oktay Karakuş, Ercan E. Kuruoğlu, Mustafa A. Altınkaya
Reversible jump Markov chain Monte Carlo (RJMCMC) is a Bayesian model estimation method which has been used for trans-dimensional sampling. In this study, we propose utilization of…