Two-stage semantic segmentation in neural networks

Diana Teixeira e Silva; Ricardo Cruz; Tiago Gonçalves; Diogo Carneiro

doi:10.1117/12.2679881

7 June 2023 Two-stage semantic segmentation in neural networks

Diana Teixeira e Silva, Ricardo Cruz, Tiago Gonçalves, Diogo Carneiro

Proceedings Volume 12701, Fifteenth International Conference on Machine Vision (ICMV 2022); 127010G (2023) https://doi.org/10.1117/12.2679881
Event: Fifteenth International Conference on Machine Vision (ICMV 2022), 2022, Rome, Italy

Abstract

Semantic segmentation consists of classifying each pixel according to a set of classes. This process is particularly slow for high-resolution images, which are present in many applications, ranging from biomedicine to the automotive industry. In this work, we propose an algorithm targeted to segment high-resolution images based on two stages. During stage 1, a lower-resolution interpolation of the image is the input of a first neural network, whose low-resolution output is resized to the original resolution. Then, in stage 2, the probabilities resulting from stage 1 are divided into contiguous patches, with less confident ones being collected and refined by a second neural network. The main novelty of this algorithm is the aggregation of the low-resolution result from stage 1 with the high-resolution patches from stage 2. We propose the U-Net architecture segmentation, evaluated in six databases. Our method shows similar results to the baseline regarding the Dice coefficient, with fewer arithmetic operations.

Citation Download Citation

Diana Teixeira e Silva, Ricardo Cruz, Tiago Gonçalves, and Diogo Carneiro "Two-stage semantic segmentation in neural networks", Proc. SPIE 12701, Fifteenth International Conference on Machine Vision (ICMV 2022), 127010G (7 June 2023); https://doi.org/10.1117/12.2679881

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