A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation.
Max-Heinrich LavesJens BickerLüder A. KahrsTobias OrtmaierPublished in: Int. J. Comput. Assist. Radiol. Surg. (2019)
Keyphrases
- comparative study
- semantic segmentation
- endoscopic images
- pascal voc
- object detection
- bag of words
- conditional random fields
- superpixels
- weakly supervised
- object categories
- image set
- object recognition
- object segmentation
- scene classification
- object classes
- object class
- region of interest
- test images
- image classification
- higher order
- brain tumors
- image segmentation
- image processing
- feature selection
- segmentation algorithm
- generative model
- co occurrence
- ground truth
- image analysis
- coronary artery