IMAGE SEGMENTATION ACCURACY DEPENDING ON THE DEPTH OF U-NET MODEL - Riekstiņš, Jevģēnijs; Kodors, Sergejs (HUMAN. ENVIRONMENT. TECHNOLOGY. Proceedings of the Students International Scientific and Practical Conference, 2020)
The aim of this work is to obtain information about impact of the depth of U-Net architecture model into segmentation accuracy. Experiment was completed using dataset of DSM images. Neural networks were trained to recognize building locations. Experiment considered to decrease the number of U-Net filter blokes to measure impact on result accuracy.