Now showing items 1-2 of 2

    • Complexification through gradual involvement and reward providing in deep reinforcement learning 

      Rulko, E. V. (БНТУ, 2024)
      Training a relatively big neural network within the framework of deep reinforcement learning that has enough capacity for complex tasks is challenging. In real life the process of task solving requires system of knowledge, where more complex skills are built upon previously learned ones. The same way biological evolution builds new forms of life based on a previously achieved ...
      2024-12-27
    • Terrain relative navigation based on deep feature template matching and visual odometry 

      Rulko, E. V. (БНТУ, 2025)
      The main hurdle for terrain relative navigation systems is the incongruity of visual features between a patch of a satellite reference map and a view from an onboard UAV camera. Images are taken during different time of year, under different weather, vegetation and lighting conditions, with different angles of observation. This work proposes the usage of deep feature template ...
      2025-04-15