Zbigniew Omiotek

Associate Professor

Lublin University of Technology

Poland

Research Interests

Explore related searches

Professors in Poland Professors in Medical Imaging Medical Imaging professors in Poland

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Dr. Zbigniew Omiotek is an Associate Professor at Lublin University of Technology, Poland. His research interests include advanced diagnostic techniques utilizing machine learning and deep learning architectures, particularly in the fields of medical imaging and materials science. Recent articles authored by Dr. Omiotek explore various applications, such as the detection of dangerous items and the diagnosis of COVID-19, as well as the analysis of cement composites and bone porosity.

Articles (11)

Year:

2025

Year:

2025

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Collaborators (3)

Andrzej Kotyra

Lublin University of Technology

POLAND

View details

Ewaryst Tkacz

Head of the Department/Titular Professor

Silesian University of Technology

POLAND

View details

Małgorzata Szafraniec

Lublin University of Technology

POLAND

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Zbigniew Omiotek

Research Interests

Explore related searches

Contact this professor

About

Articles (11)

Effectiveness of Modern Models Belonging to the YOLO and Vision Transformer Architectures in Dangerous Items Detection

Comparison of Modern Convolution and Transformer Architectures: YOLO and RT-DETR in Meniscus Diagnosis

Water absorption prediction of nanopolymer hydrophobized concrete surface using texture analysis and machine learning algorithms

A Novel COVID-19 Diagnosis Approach Utilizing a Comprehensive Set of Diagnostic Information (CSDI)

Comparison of the Classification Results Accuracy for CT Soft Tissue and Bone Reconstructions in Detecting the Porosity of a Spongy Tissue

Application of Deep Convolutional Neural Networks in the Diagnosis of Osteoporosis

Flame Image Processing and Classification Using a Pre-Trained VGG16 Model in Combustion Diagnosis

Combustion process monitoring based on flame intensity time series

3D visualization of human body internal structures surface during stereo-endoscopic operations using computer vision techniques

An integrated texture analysis and machine learning approach for durability assessment of lightweight cement composites with hydrophobic coatings modified by nanocellulose

Fractal analysis as a method for feature extraction in detecting osteoporotic bone destruction

Collaborators (3)

Andrzej Kotyra

Ewaryst Tkacz

Małgorzata Szafraniec

Make your next move.