Greenery Segmentation In Urban Images By Deep Learning
This work addresses vegetation measurement in urban environments, but it is incremental as it builds on existing deep learning methods.
The paper tackled the problem of greenery segmentation in urban images to estimate the Green View Index, improving upon previous results by leveraging deep learning networks with a weighting strategy in the loss function.
Vegetation is a relevant feature in the urban scenery and its awareness can be measured in an image by the Green View Index (GVI). Previous approaches to estimate the GVI were based upon heuristics image processing approaches and recently by deep learning networks (DLN). By leveraging some recent DLN architectures tuned to the image segmentation problem and exploiting a weighting strategy in the loss function (LF) we improved previously reported results in similar datasets.