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Machine Vision Group

Department of Automatics and Robotics – Computer Vision Lab
Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering
AGH University of Science and Technology


The Machine Vision Research Group (MVG Group) focuses on interdisciplinary research problems from the field of machine vision and medicine. The problems are solved using methods of digital image processing and analysis, machine learning and deep learning.

Team

Joanna Jaworek-Korjakowska,
Associate professor
(dr hab. inż., prof. Uczelni)
Paweł Kłeczek, PhD Anna Wójcicka, PhD
Dariusz Kucharski, MSc
PhD candidate
Andrzej Brodzicki, MSc
PhD candidate
Michał Piekarski, MSc
PhD candidate
Aleksander Kostuch, MSc
PhD candidate
Maciej Aleksandrowicz, MSc
PhD candidate

Contact

Aktualności

[2022-01-04] Scholarship at Stanford University for Joanna Jaworek-Korjakowska

Another great success in our team! Dr hab. inż. Joanna Jaworek-Korjakowska recieved a scholarship in the IV Edition of a Bekker Programme run by NAWA (Polish National Agency for Academic Exchange). She will be doing a three-month long research project in one of the most prestigious institutions in the wold - Stanford University, USA. You can read more about the Bekker Programme here

[2022-01-02] New Publication in Medical Image Analysis Journal

Our latest article: Analysis of the ISIC image datasets: usage, benchmarks and recommendations has been accepted by Medical Image Analysis Journal, which is one of the most influential publishers in the field (IF 8.545). This work was a result of a partnership between Joanna Jaworek-Korjakowska and Andrzej Brodzicki with researchers from Manchester Metropolitan University (Bill Cassidy, Connah Kendrick and Moi Hoon Yap). We hope it is just the beggining of a great colaboration between our two institutions. You can check the full paper in the following link

[2021-10-30] Grant NCBiR we współpracy z firmą Onwelo

Our team participates in an industry research project funded by NCBiR (The National Centre for Research and Development) - “X-rAI: Przeglądarka diagnostyczna dla radiologii z komputerowym wspomaganiem wykorzystującym Sztuczną Inteligencję (Diagnostic viewer for radiology with computer-assistance using Artificial Intelligence)” - POIR.01.01.01-00-1666/20 (PI: Prof. dr hab. inż. Z. Tabor, dr hab. A. Krzyżak, Co-I: dr hab. inż. J. Jaworek-Korjakowska). The aim of the project is to develop a deep learning browser to assist the radiologist in the diagnosis of lung and liver cancer. The project will analyze images from computed tomography and magnetic resonance imaging. New 3D Multi-view CNN architectures will be proposed and tested.

[2021-04-20] CVPR 2021 - SAIAD Workshop

We received nice news that the article entitled “SafeSO: Interpretable and Explainable Deep Learning Approach for Seat Occupancy Classification in Vehicle Interior” by Joanna Jaworek-Korjakowska, Aleksander Kostuch and Paweł Skruch was accepted at the prestigious IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'2021, CORE A *), SAIAD workshop. Looking at the list of accepted works (NVIDIA, Fraunhofer, BMW, VW, TUM) it should be stated that we found ourselves in a very good company.

[2021-04-20] Grant FAST Healthcare Network Plus - EPSRC, United Kingdom

Miło nam poinformować, że otrzymaliśmy projekt Early detection of skin cancer by using mobile devices at point of care, FAST Healthcare Network Plus, finansowanym przez brytyjską instytucję EPSRC (Engineering and Physical Sciences Research Council). W ramach projektu biorą udział J. Jaworek-Korjakowska (Co-I, Kierownik AGH) i A. Brodzicki. Podejmowane działania dotyczą badań nad lokalizacjami zmian skórnych, analizie występowania duplikatów w bazach ISIC, a także implementacji na urządzeniach mobilnych aplikacji do rozpoznawania nowotworów skóry. Projekt jest realizowany we współpracy z naukowcami z Manchester Metropolitan University. Kierownikiem (PI) projektu jest Prof. Moi Hoon Yap.

start.txt · Last modified: 2022/02/18 16:31 by abrodzicki