About the CoDIS Lab

CoDIS stands for Computational Data and Image Sciences.

CoDIS Lab is the umbrella name, for my research, the areas of which span Statistical Signal/Image Processing, Environmental Remote Sensing, Sports Analytics, Data Science, Bayesian Data Analysis, Inverse problems, and Uncertainty Quantification.

The primary research under the CoDIS Lab consists of three main areas

  • Remote Sensing Imaging for Environmental Applications
  • Applied Bayesian Statistics
  • Sports Analytics
  • There is also a secondary research is being conducted in areas of

  • Computational Data Science
  • Medical Imaging
  • Codes for published works can be found in CoDIS Lab Github Page.


    Talks


    Important Publications

    For all my papers, see my google scholar Google Scholar page.

    2023

  • On Advances, Challenges and Potentials of Remote Sensing Image Analysis in Marine Debris and Suspected Plastics Monitoring. J. O. Karakuş. Frontiers in Remote Sensing. 2023. [PDF]
  • A machine learning approach for player and position Adjusted Expected goals in football (Soccer). J. H. Hewitt, and O. Karakuş. Franklin Open. 2023. [PDF]
  • Predicting air quality via multimodal AI and satellite imagery. A. Rowley, and O. Karakuş. Remote Sensing of Environment. 2023. [PDF]
  • A hybrid particle-stochastic map filter. P. Hao, O. Karakuş, and A. Achim. Signal Processing. 2023. [PDF]
  • High-precision density mapping of marine debris and floating plastics via satellite imagery. H. Booths, W. Ma, and O. Karakuş. Scientific Reports (Nature). 2023. [PDF]
  • Sentiment analysis for measuring hope and fear from Reddit posts during the 2022 Russo-Ukrainian conflict. A. Guerra, and O. Karakuş. Frontiers in Artificial Intelligence. 2023. [PDF]
  • 2020 - 2022

  • AMM-FuseNet: Attention-Based Multi-Modal Image Fusion Network for Land Cover Mapping. W. Ma, O. Karakuş, and P. L. Rosin. Remote Sensing. 2022. [PDF]
  • Cauchy-Rician Model for Backscattering in Urban SAR Images. O. Karakuş, E. E. Kuruoğlu, A. Achim and M. A. Altınkaya. IEEE Geoscience and Remote Sensing Letters. 2022. [BibTeX]
  • Representation Learning via Cauchy Convolutional Sparse Coding. P. Mayo, O. Karakuş, R. Holmes and A. Achim. IEEE Access. 2021. [PDF] [BibTeX][CODE]
  • On Solving SAR Imaging Inverse Problems Using Non-Convex Regularisation with a Cauchy-based Penalty. O. Karakuş, and A. Achim. IEEE Transactions on Geoscience and Remote Sensing. 2021. [PDF] [BibTeX][CODE]
  • Exploiting the Dual-Tree Complex Wavelet Transform for Ship Wake Detection in SAR Imagery W. Ma, A. Achim and O. Karakuş. ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021. [PDF][BibTeX]
  • A Generalized Gaussian Extension to the Rician Distribution for SAR Image Modeling. O. Karakuş, E. E. Kuruoglu, and A. Achim. IEEE Transactions on Geoscience and Remote Sensing. 2021. [PDF][BibTeX] [CODE]
  • Current Advances in Computational Lung Ultrasound Imaging: A Review T. Yang, O. Karakuş, N. Anantrasirichai, A. Achim. arXiv preprint. 2022. [PDF]
  • [BIBTEX]
  • Modeling and SAR Imaging of the Sea Surface: a Review of the State-of-the-Art with Simulations I. Rizaev, O. Karakuş, S. J. Hogan, A. Achim. ISPRS Journal of Photogrammetry and Remote Sensing. 2022. [PDF]
  • Convergence guarantees for non-convex optimisation with Cauchy-based penalties. O. Karakuş, P. Mayo, and A. Achim. IEEE Transactions on Signal Processing. 2020.[PDF] [BibTeX] [CODE]
  • Detection of Line Artefacts in Lung Ultrasound Images of COVID-19 Patients via Non-Convex Regularization. O. Karakuş, N. Anantrasirichai, A. Aguersif, S. Silva, A. Basarab and A Achim. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 2020.[PDF] [BibTeX] [CODE]
  • Ship Wake Detection in SAR Images via Sparse Regularization. O. Karakuş, I. Rizaev, and A. Achim. IEEE Transactions on Geoscience and Remote Sensing. 2020. [PDF] [BibTeX] [CODE]