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The problem of visual pollution is a growing concern in urban areas, characterized by intrusive visual elements that can lead to overstimulation and distraction, obstructing views and causing distractions for drivers. Large‐area advertising structures, such as billboards, while being effective advertisement mediums, are significant contributors to visual pollution. Illegally placed or huge billboards can also exacerbate those issues and pose safety hazards. Therefore, there is a pressing need for effective and efficient methods to identify and manage advertising structures in urban areas. This article proposes a deep‐learning‐based system for automatically detecting billboards using consumer‐grade unmanned aerial vehicles. Thanks to the geospatial information from the drone's sensors, the position of billboards can be estimated. Side by side with the system, we share the very first dataset for billboard detection from a drone view. It contains 1361 images supplemented with spatial metadata, together with 5210 annotations. [ABSTRACT FROM AUTHOR]

Autonomous lunar exploration is a complex task that requires the development of sophisticated algorithms to control the movement of lunar rovers in a challenging environment, based on visual feedback. To train and evaluate these algorithms, it is crucial to have access to both a simulation framework and data that accurately represent the conditions on the lunar surface, with the main focus on providing the visual fidelity necessary for computer vision algorithm development. In this paper, we present a lunar-orientated robotic simulation environment, developed using the Unity game engine, built on top of robot operating system 2 (ROS 2), which enables researchers to generate quality synthetic vision data and test their algorithms for autonomous perception and navigation of lunar rovers in a controlled environment. To demonstrate the versatility of the simulator, we present several use cases in which it is deployed on various efficient hardware platforms, including FPGA and Edge AI devices, to evaluate the performance of different vision-based algorithms for lunar exploration. In general, the simulation environment provides a valuable tool for researchers developing lunar rover systems. [ABSTRACT FROM AUTHOR]

Competing Interests: The authors declare no conflict of interest.