Crowdsourcing annotation system of object counting dataset for deep learning algorithm
Tjeng Wawan Cenggoro, Fidelson Tanzil, Ayu Hidayah Aslamiah, Ettikan Kandasamy Karuppiah, Bens Pardamean · IOP Conference Series Earth and Environmental Science · 2018
Deep Learning is currently the state-of-the-art technique for various Computer Vision tasks, including object counting. Despite of its high performance, Deep Learning requires a gigantic amount of training data to show its best result. Getting this massive data in reasonable time requires a proper strategy such as crowdsourcing. However, in case of object counting, we found no crowdsourcing system able to effectively collect necessary data. To tackle this problem, we develop a crowdsourcing system to annotate image for object counting dataset. This system is also equipped with validation system to ensure the quality of collected dataset.