[HTML][HTML] Deep learning approaches to biomedical image segmentation
IRI Haque, J Neubert - Informatics in Medicine Unlocked, 2020 - Elsevier
The review covers automatic segmentation of images by means of deep learning
approaches in the area of medical imaging. Current developments in machine learning …
approaches in the area of medical imaging. Current developments in machine learning …
Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective
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 …
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …
Remote sensing image segmentation advances: A meta-analysis
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 …
production of very high spatial resolution multispectral images. In order to adapt to this rapid …
Landslide detection using multi-scale image segmentation and different machine learning models in the higher himalayas
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 …
are needed to document the occurrence and extent of landslides and to investigate their …
Object-based land cover classification of cork oak woodlands using UAV imagery and Orfeo ToolBox
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) …
geographical object-based image classification (GEOBIA) of very high resolution (VHR) …
Data and resolution requirements in map** vegetation in spatially heterogeneous landscapes
A Räsänen, T Virtanen - Remote Sensing of Environment, 2019 - Elsevier
It has been argued that even centimeter-level resolution is needed for map** vegetation
patterns in spatially heterogeneous landscapes such as northern peatlands. However, there …
patterns in spatially heterogeneous landscapes such as northern peatlands. However, there …
Assessment of land cover change and its impact on changes in soil erosion risk in Nepal
K Uddin, M Abdul Matin, S Maharjan - Sustainability, 2018 - mdpi.com
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 …
topsoil has a direct and indirect effect on human life and livelihoods. The present study …
Accounting for training data error in machine learning applied to earth observations
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 …
dynamics and create continuous and categorical maps of biophysical properties and land …
Comparison and assessment of different object-based classifications using machine learning algorithms and UAVs multispectral imagery: A case study in a citrus …
This study aimed to compare and assess different Geographic Object-Based Image Analysis
(GEOBIA) and machine learning algorithms using unmanned aerial vehicles (UAVs) …
(GEOBIA) and machine learning algorithms using unmanned aerial vehicles (UAVs) …
DIAL: Deep interactive and active learning for semantic segmentation in remote sensing
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 …
human in the loop to swiftly obtain accurate segmentation maps of remote sensing images …