Rok 2024

• Vehicle type recognition: a case study of MobileNetV2 for an image Classification task

  Publikacja

  • D. Kobiela
  • J. Groth
  • M. Hajdasz
  • M. Erezman

  - Procedia Computer Science - Rok 2024

  The goal of the research was to demonstrate the full data science lifecycle through a use case of the MobileNetv2 model for vehicle image Classification task using various validation and test sets, each with different difficulty level. Diverse model variations were employed, each designed to recognize images of ground vehicles and classify them into one of five possible classes: car, truck, motorcycle, bicycle, or bus. In terms...

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Rok 2023

• Neural Graph Collaborative Filtering: Analysis of Possibilities on Diverse Datasets

  Publikacja

  • D. Kobiela
  • J. Groth
  • M. Sieczczyński
  • R. Wolniak
  • K. Pastuszak

  - Rok 2023

  This paper continues the work by Wang et al. [17]. Its goal is to verify the robustness of the NGCF (Neural Graph Collaborative Filtering) technique by assessing its ability to generalize across different datasets. To achieve this, we first replicated the experiments conducted by Wang et al. [17] to ensure that their replication package is functional. We received sligthly better results for ndcg@20 and somewhat poorer results for...

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