"Yamac, Mehmet" - Selaus tekijän mukaan TUNICRIS-julkaisut
Viitteet 1-10 / 10
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Advance Warning Methodologies for COVID-19 Using Chest X-Ray Images
(2021)
article<p>Coronavirus disease 2019 (COVID-19) has rapidly become a global health concern after its first known detection in December 2019. As a result, accurate and reliable advance warning system for the early diagnosis of ... -
Convolutional Sparse Support Estimator Network (CSEN): From Energy-Efficient Support Estimation to Learning-Aided Compressive Sensing
(2021)
article<p>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 ... -
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
(05 / 2021)
article<p>Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ... -
COVID-19 infection map generation and detection from chest X-ray images
(01.04.2021)
article<p>Computer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment and prevent the spread of the virus. Numerous studies have proposed to use Deep ... -
Generalized Tensor Summation Compressive Sensing Network (GTSNET): An Easy to Learn Compressive Sensing Operation
(2023)
article<p>The efforts in compressive sensing (CS) literature can be divided into two groups: finding a measurement matrix that preserves the compressed information at its maximum level, and finding a robust reconstruction algorithm. ... -
Multi-Level Reversible Data Anonymization via Compressive Sensing and Data Hiding
(2021)
article<p>Recent advances in intelligent surveillance systems have enabled a new era of smart monitoring in a wide range of applications from health monitoring to homeland security. However, this boom in data gathering, analyzing ... -
Operational Neural Networks for Parameter-Efficient Hyperspectral Single-Image Super-Resolution
(15.11.2023)
article<p>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. ... -
Operational Support Estimator Networks
(30.05.2024)
article<p>In this work, we propose a novel approach called Operational Support Estimator Networks (OSENs) for the support estimation task. Support Estimation (SE) is defined as finding the locations of non-zero elements in sparse ... -
Representation based regression for object distance estimation
(01 / 2022)
article<p>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). ... -
Super Neurons
(2023)
article<p>Self-Organized Operational Neural Networks (Self-ONNs) have recently been proposed as new-generation neural network models with nonlinear learning units, i.e., the generative neurons that yield an elegant level of ...
