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Found 9 papers, 5 papers with code
Multi-label Video Classification for Underwater Ship Inspection
Today ship hull inspection including the examination of the external coating, detection of defects, and other types of external degradation such as corrosion and marine growth is conducted underwater by means of Remotely Operated Vehicles (ROVs).
Evaluating clinical diversity and plausibility of synthetic capsule endoscopic images
Like training in other modalities such as traditional endoscopy, CT, MRI, etc., a WCE training protocol would require an atlas comprising of a large corpora of images that show vivid descriptions of pathologies and abnormalities, ideally observed over a period of time.
This changes to that : Combining causal and non-causal explanations to generate disease progression in capsule endoscopy
Due to the unequivocal need for understanding the decision processes of deep learning networks, both modal-dependent and model-agnostic techniques have become very popular.
From Labels to Priors in Capsule Endoscopy: A Prior Guided Approach for Improving Generalization with Few Labels
Prior works have considered using higher quality and quantity of labels as a way of tackling the lack of generalization, however this is hardly scalable considering pathology diversity not to mention that labeling large datasets encumbers the medical staff additionally.
Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy
The progress in Computer Aided Diagnosis (CADx) of Wireless Capsule Endoscopy (WCE) is thwarted by the lack of data.
2018 Robotic Scene Segmentation Challenge
In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward kinematics and instrument CAD models.
Variational Approach for Capsule Video Frame Interpolation
The main objective of the paper is to increase the frame rate to be closer to that of the colonoscopy.
Stochastic Capsule Endoscopy Image Enhancement
In this paper, we consider the problem of enhancing the visibility of detail and shadowed tissue surfaces for capsule endoscopy images.
Y-Net: A deep Convolutional Neural Network for Polyp Detection
To handle this problem, we propose a novel deep learning method Y-Net that consists of two encoder networks with a decoder network.
