Operational Neural Networks for Parameter-Efficient Hyperspectral Single-Image Super-Resolution

Autor: Alexander Ulrichsen, Paul Murray, Stephen Marshall, Moncef Gabbouj, Serkan Kiranyaz, Mehmet Yamac, Nour Aburaed

Publikováno v: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 1470-1484 (2024)

Hyperspectral imaging is a crucial tool in remote sensing, which captures far more spectral information than standard color images. However, the increase in spectral information comes at the cost of spatial resolution. Super-resolution is a popular t

Externí odkaz: https://doaj.org/article/0f52d6eb2c5d40ac9d8052a8781eeee2

Reference-Based Blind Super-Resolution Kernel Estimation

Autor: Mehmet Yamac, Aakif Nawaz, Baran Ataman

Publikováno v: 2022 IEEE International Conference on Image Processing (ICIP).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d33ab25d5b128fd53b6f5adfef8ffa9a
https://doi.org/10.1109/icip46576.2022.9897801

Representation based regression for object distance estimation

Autor: Mete Ahishali, Mehmet Yamac, Serkan Kiranyaz, Moncef Gabbouj

Publikováno v: Neural networks : the official journal of the International Neural Network Society. 158

In this study, we propose a novel approach to predict the distances of the detected objects in an observed scene. The proposed approach modifies the recently proposed Convolutional Support Estimator Networks (CSENs). CSENs are designed to compute a d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2e9401debdcd3652d45de2ee7264071
https://pubmed.ncbi.nlm.nih.gov/36436302

Medical image analysis

Autor: Aysen Degerli, Mehmet Yamac, Mete Ahishali, Serkan Kiranyaz, Moncef Gabbouj

Publikováno v: Degerli, A, Yamac, M, Ahishali, M, Kiranyaz, S & Gabbouj, M 2022, Medical image analysis . in A Iosifidis & A Tefas (eds), Deep Learning for Robot Perception and Cognition . Academic Press, pp. 541-577 . https://doi.org/10.1016/B978-0-32-385787-1.00025-7

This chapter presents deep learning methodologies for medical imaging tasks. The chapter starts with echocardiography for early detection of myocardial infarction (MI) or commonly known as heart attack. Early and fundamental signs of MI can be visibl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::243cdfe527c9547751559ee84eb3bb4e
https://cris.vtt.fi/en/publications/a7cefba7-c7d9-462c-81ec-cefb15f2a7ea

Convolutional Sparse Support Estimator Network (CSEN): From Energy-Efficient Support Estimation to Learning-Aided Compressive Sensing

Autor: Serkan Kiranyaz, Moncef Gabbouj, Mete Ahishali, Mehmet Yamac

Publikováno v: IEEE transactions on neural networks and learning systems.

Support estimation (SE) of a sparse signal refers to finding the location indices of the nonzero elements in a sparse representation. Most of the traditional approaches dealing with SE problems are iterative algorithms based on greedy methods or opti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4925803a7ce5af5edc4f026e59b0b9d
https://pubmed.ncbi.nlm.nih.gov/34260360