Name
Title | ||
|---|---|---|
Environmental microorganism classification using conditional random fields and deep convolutional neural networks. |
Abstract | ||
|---|---|---|
•Application of content-based image analysis to Environmental Microorganism (EM) classification which plays a fundamental role for establishing sustainable ecosystem.•Building an effective pixel-level feature extractor from scarce training images, by re-purposing a Deep Convolutional Neural Netwrok (DCNN) pre-trained for image classification using large auxiliary data.•Integration of global features to improve the segmentation quality by providing long-range consistencies among pixel labels•Usage of a Conditional Random Field (CRF) to jointly localize and classify EMs by considering the spatial relations among pixel-level features, and their relations to global features. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.patcog.2017.12.021 | Pattern Recognition |
Keywords | Field | DocType |
Environmental microorganism,Conditional random fields,Global feature extraction,Image classification,Image segmentation | Spatial relation,Conditional random field,Microorganism classification,Pattern recognition,Segmentation,Convolutional neural network,Artificial intelligence,Extractor,Contextual image classification,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
77 | 1 | 0031-3203 |
Citations | PageRank | References |
2 | 0.41 | 30 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergey Kosov | 1 | 4 | 1.11 |
| Kimiaki Shirahama | 2 | 108 | 22.43 |
| Chen Li | 3 | 4 | 5.18 |
| Marcin Grzegorzek | 4 | 185 | 48.00 |