The review covers automatic segmentation of images by means of deep learning
approaches in the area of medical imaging. Current developments in machine learning …

Image segmentation is a critical and important step in (GEographic) Object-Based Image
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …

The advances in remote sensing sensors during the last two decades have led to the
production of very high spatial resolution multispectral images. In order to adapt to this rapid …

Landslides represent a severe hazard in many areas of the world. Accurate landslide maps
are needed to document the occurrence and extent of landslides and to investigate their …

This paper investigates the reliability of free and open-source algorithms used in the
geographical object-based image classification (GEOBIA) of very high resolution (VHR) …

It has been argued that even centimeter-level resolution is needed for mapping vegetation
patterns in spatially heterogeneous landscapes such as northern peatlands. However, there …

Land cover change is a critical driver for enhancing the soil erosion risk in Nepal. Loss of the
topsoil has a direct and indirect effect on human life and livelihoods. The present study …

Remote sensing, or Earth Observation (EO), is increasingly used to understand Earth system
dynamics and create continuous and categorical maps of biophysical properties and land …

This study aimed to compare and assess different Geographic Object-Based Image Analysis
(GEOBIA) and machine learning algorithms using unmanned aerial vehicles (UAVs) …

In this article, we propose to build up a collaboration between a deep neural network and a
human in the loop to swiftly obtain accurate segmentation maps of remote sensing images …