Automated detection of malaria parasites on thick blood smears via mobile devices

L Rosado, JMC Da Costa, D Elias… - Procedia Computer …, 2016 - Elsevier
An estimated 214 million cases of malaria were detected in 2015, which caused
approximately 438 000 deaths. Around 90% of those cases occurred in Africa, where the …

Mobile-based analysis of malaria-infected thin blood smears: automated species and life cycle stage determination

L Rosado, JMC Da Costa, D Elias, JS Cardoso - Sensors, 2017 - mdpi.com
Microscopy examination has been the pillar of malaria diagnosis, being the recommended
procedure when its quality can be maintained. However, the need for trained personnel and …

Adaptive scale selection for multiscale segmentation of satellite images

J Li, L Feng, X Zhang, X Hu - IEEE Journal of Selected Topics …, 2017 - ieeexplore.ieee.org
With dramatically increasing of the spatial resolution of satellite imaging sensors, object-
based image analysis (OBIA) has been gaining prominence in remote sensing applications …

Semantic segmentation of remote sensing imagery using an object-based Markov random field model with auxiliary label fields

C Zheng, Y Zhang, L Wang - IEEE Transactions on geoscience …, 2017 - ieeexplore.ieee.org
The Markov random field (MRF) model has attracted great attention in the field of image
segmentation. However, most MRF-based methods fail to resolve segmentation …

Semantic segmentation of remote sensing imagery using object-based Markov random field model with regional penalties

C Zheng, L Wang - IEEE Journal of Selected Topics in Applied …, 2014 - ieeexplore.ieee.org
This paper proposes a novel object-based Markov random field model (OMRF) for semantic
segmentation of remote sensing images. First, the method employs the region size and edge …

A Markov random field integrating spectral dissimilarity and class co-occurrence dependency for remote sensing image classification optimization

L Wang, X Huang, C Zheng, Y Zhang - ISPRS Journal of Photogrammetry …, 2017 - Elsevier
This paper develops a novel Markov Random Field (MRF) model for edge-preserving spatial
regularization of classification maps. MRF methods based on the uniform smoothness lead …

Segmentation for remote-sensing imagery using the object-based Gaussian-Markov random field model with region coefficients

C Zheng, H Yao - International Journal of Remote Sensing, 2019 - Taylor & Francis
The Markov random field (MRF) model is a widely used method for remote-sensing image
segmentation, especially the object-based MRF (OMRF) method has attracted great …

Constructing hierarchical segmentation tree for feature extraction and land cover classification of high resolution MS imagery

L Wang, Q Dai, Q Xu, Y Zhang - IEEE Journal of Selected …, 2015 - ieeexplore.ieee.org
Accurate interpretation of high spatial resolution multispectral (MS) imagery relies on the
extraction and fusion of information obtained from both spectral and spatial domains …

Image segmentation: A survey

KM Pooja, R Rajesh - Recent Advances in Mathematics, Statistics …, 2016 - World Scientific
Segmentation is needed for extracting the useful or concerned information. There are lots of
segmentation algorithms available. Here, we have discussed various segmentation …

Federated filter algorithm with positioning technique based on 3D sensor

G Dai, L Yu, H Xu, Z Hou, S Fei - Circuits, Systems, and Signal Processing, 2018 - Springer
Somatosensory control based on 3D sensors has been widely used as a virtual reality and
motion capture technology in large-screen human–computer interactive systems. However …