Ensemble of Deep Convolutional Neural Networks with Monte Carlo Dropout Sampling for Automated Image Segmentation Quality Control and Robust Deep Learning Using Small Datasets.
Evan HannRicardo A. GonzalesIulia A. PopescuQiang ZhangVanessa M. FerreiraStefan K. PiechnikPublished in: MIUA (2021)
Keyphrases
- monte carlo
- deep learning
- quality control
- image segmentation
- restricted boltzmann machine
- convolutional neural networks
- machine vision
- unsupervised feature learning
- importance sampling
- adaptive sampling
- markov chain
- deep architectures
- unsupervised learning
- machine learning
- manufacturing systems
- graph cuts
- deep belief networks
- mental models
- particle filter
- learning algorithm
- monte carlo tree search
- image processing
- markov random field
- weakly supervised
- multiscale
- sampling methods
- segmentation method
- segmentation algorithm
- markov chain monte carlo
- partial occlusion
- computer vision
- semi supervised
- principal component analysis
- expectation maximization
- graphical models