Search Results for author:
Found 3 papers, 0 papers with code
Segmentation of Weakly Visible Environmental Microorganism Images Using Pair-wise Deep Learning Features
The use of PDLFs enables the network to focus more on the foreground (EMs) by concatenating the pairwise deep learning features of each image to different blocks of the base model SegNet.
A New Pairwise Deep Learning Feature For Environmental Microorganism Image Analysis
In order to fasten, low the cost, increase consistency and accuracy of identification, we propose the novel pairwise deep learning features to analyze microorganisms.
A two-layer Conditional Random Field for the classification of partially occluded objects
Conditional Random Fields (CRF) are among the most popular techniques for image labelling because of their flexibility in modelling dependencies between the labels and the image features.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
