A Deep Learning Approach to Enhance Semantic Segmentation of Bacteria and Pus Cells from Microscopic Urine Smear Images Using Synthetic Data.
Vidyashree R. KanaburDeepu VijayasenanSumam David SSreejith GovindanPublished in: CVIP (1) (2023)
Keyphrases
- synthetic data
- deep learning
- blood cells
- semantic segmentation
- real world
- image database
- input image
- data sets
- weakly supervised
- object recognition
- image retrieval
- image understanding
- image features
- image classification
- image set
- multiple images
- test images
- text mining
- conditional random fields
- co occurrence
- image annotation
- object categories
- object classes
- multiple objects
- bounding box
- superpixels
- unsupervised learning
- image processing
- machine learning