Distributed sensor networks have the ability for more data collection and advanced tasks such as object recognition and tracking than a singular sensor. However, these sensor networks are often limited in their ability to coordinate either by their requirement to be connected to a central system or by their fixed position and static nature. Drones or unmanned aerial vehicles (UAVs) provide a unique opportunity in multi-sensor networks. Although drones are usually limited by their available power due to battery capacity, recent advances in technology and algorithms provide drones with more available computational power. In addition to computability augmentation in drone mobility, decentralized coordination enables drones to create the next generation of distributed multi-sensor networks. In this paper, we explore combination of the existing image processing and object recognition techniques in the perspective of collaborative drones, which can improve the robustness of image recognition tasks.