Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

Equipment

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Image classification methods for the imbalanced data

2017/27/N/ST6/01705

Keywords:

artificial intelligence machine learning image recognition imbalanced data

Descriptors:

  • ST6_7: Artificial intelligence, intelligent systems, multi-agent systems
  • ST6_8: Computer graphics, image processing, computer vision, multimedia, computer games
  • ST6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)

Panel:

ST6 - Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

Host institution :

Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie, Wydział Informatyki, Elektroniki i Telekomunikacji

woj. małopolskie

Other projects carried out by the institution 

Principal investigator (from the host institution):

Michał Koziarski 

Number of co-investigators in the project: 2

Call: PRELUDIUM 14 - announced on 2017-09-15

Amount awarded: 163 660 PLN

Project start date (Y-m-d): 2018-07-23

Project end date (Y-m-d): 2022-07-22

Project duration:: 48 months (the same as in the proposal)

Project status: Project settled

Project description

Download the project description in a pdf file

Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Equipment purchased [PL]

  1. Stacja robocza do obliczeń głębokich z monitorem (28 000 PLN)

Information in the final report

  • Publication in academic press/journals (4)
  • Articles in post-conference publications (5)
  1. RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification
    Authors:
    Michał Koziarski, Colin Bellinger, Michał Woźniak
    Academic press:
    Machine Learning (rok: 2021, tom: 110, strony: 3059–3093), Wydawca: Springer
    Status:
    Published
    DOI:
    10.1007/s10994-021-06012-8 - link to the publication
  2. Potential Anchoring for imbalanced data classification
    Authors:
    Michał Koziarski
    Academic press:
    Pattern Recognition (rok: 2021, tom: 120, strony: 108114), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.patcog.2021.108114 - link to the publication
  3. Radial-Based Undersampling for imbalanced data classification
    Authors:
    Michał Koziarski
    Academic press:
    Pattern Recognition (rok: 2020, tom: 102, strony: 107262), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.patcog.2020.107262 - link to the publication
  4. Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise
    Authors:
    Michał Koziarski, Michał Woźniak, Bartosz Krawczyk
    Academic press:
    Knowledge-Based Systems (rok: 2020, tom: 204, strony: 106223), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.knosys.2020.106223 - link to the publication
  1. CSMOUTE: Combined Synthetic Oversampling and Undersampling Technique for Imbalanced Data Classification
    Authors:
    Michał Koziarski
    Conference:
    2021 International Joint Conference on Neural Networks (IJCNN) (rok: 2021, ), Wydawca: IEEE
    Data:
    konferencja 18-22 Jul 2021
    Status:
    Published
    DOI:
    link to the publication
  2. Convolutional Neural Network-Based Classification of Histopathological Images Affected by Data Imbalance
    Authors:
    Michał Koziarski, Bogdan Kwolek, Bogusław Cyganek
    Conference:
    24th International Conference on Pattern Recognition, The Second International Workshop on Deep Learning for Pattern Recognition (rok: 2018, ), Wydawca: Springer
    Data:
    konferencja 43332
    Status:
    Published
  3. The Choice of Feature Representation in Small-Scale MobileNet-Based Imbalanced Image Recognition
    Authors:
    Michał Koziarski, Bogusław Cyganek, Kazimierz Wiatr
    Conference:
    15th International Conference on Computer Vision Theory and Applications (rok: 2020, ), Wydawca: Springer
    Data:
    konferencja 27-29 Feb 2020
    Status:
    Published
  4. Two-Stage Resampling for Convolutional Neural Network Training in the Imbalanced Colorectal Cancer Image Classification
    Authors:
    Michał Koziarski
    Conference:
    2021 International Joint Conference on Neural Networks (IJCNN) (rok: 2021, ), Wydawca: IEEE
    Data:
    konferencja 18-22 Jul 2021
    Status:
    Published
    DOI:
    link to the publication
  5. Radial-Based Undersampling Algorithm for Classification of Breast Cancer Histopathological Images Affected by Data Imbalance
    Authors:
    Michał Koziarski
    Conference:
    12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (rok: 2019, ), Wydawca: IEEE
    Data:
    konferencja 19-21 Oct 2019
    Status:
    Published

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