Rok 2023

• Predicting emotion from color present in images and video excerpts by machine learning

  Publikacja

  • A. Wędołowska
  • D. Weber
  • B. Kostek

  - IEEE Access - Rok 2023

  This work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...

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Rok 2022

• AITP - AI Thermal Pedestrians Dataset

  Publikacja

  • A. Górska
  • P. Guzal
  • A. Wędołowska
  • M. Włoszczyńska
  • J. Rumiński

  - Rok 2022

  Efficient pedestrian detection is a very important task in ensuring safety within road conditions, especially after sunset. One way to achieve this goal is to use thermal imaging in conjunction with deep learning methods and an annotated dataset for models training. In this work, such a dataset has been created by capturing thermal images of pedestrians in different weather and traffic conditions. All images were manually annotated...

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• Pedestrian detection in low-resolution thermal images

  Publikacja

  • A. Górska
  • P. Guzal
  • I. Namiotko
  • A. Wędołowska (dawniej: J. Rumiński)
  • M. Włoszczyńska
  • J. Rumiński

  - Rok 2022

  Over one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...

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