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Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection
TLDR
In this paper, we present a Deep Autoencoding Gaussian Mixture Model (DAGMM) for unsupervised anomaly detection. Expand
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Optimal Multiple Surface Segmentation With Shape and Context Priors
TLDR
A graph-theoretic framework for multi-object segmentation that incorporates both shape and context prior knowledge in a 3-D graph representation to help overcome the stated challenges. Expand
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Globally Optimal Tumor Segmentation in PET-CT Images: A Graph-Based Co-segmentation Method
TLDR
Tumor segmentation in PET and CT images is notoriously challenging due to the low spatial resolution in PET images. Expand
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Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning
TLDR
Risk stratification of lung nodules is a task of primary importance in lung cancer diagnosis. Expand
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On the entropy for Atanassov's intuitionistic fuzzy sets: An interpretation from the perspective of amount of knowledge
  • K. Guo, Q. Song
  • Mathematics, Computer Science
  • Appl. Soft Comput.
  • 1 November 2014
TLDR
A real-life example is provided for a discussion on the application of the models.Develop new entropy of A-IFSs to overcome the drawbacks the existing ones bring about. Expand
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Vessel Boundary Delineation on Fundus Images Using Graph-Based Approach
TLDR
This paper proposes an algorithm to measure the width of retinal vessels in fundus photographs using graph-based algorithm to segment both vessel edges simultaneously. Expand
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Data-Based Fault-Tolerant Control of High-Speed Trains With Traction/Braking Notch Nonlinearities and Actuator Failures
  • Q. Song, Y. Song
  • Computer Science, Medicine
  • IEEE Transactions on Neural Networks
  • 1 December 2011
TLDR
This paper investigates the position and velocity tracking control problem of high-speed trains with multiple vehicles connected through couplers. Expand
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Optimal Graph Search Segmentation Using Arc-Weighted Graph for Simultaneous Surface Detection of Bladder and Prostate
TLDR
We present a novel method for globally optimal surface segmentation of multiple mutually interacting objects, incorporating both edge and shape knowledge in a 3-D graph-theoretic approach. Expand
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Segmentation of pathological and diseased lung tissue in CT images using a graph-search algorithm
TLDR
This paper presents an automatic algorithm for pathological lung CT image segmentation that uses a graph search driven by a cost function combining the intensity, gradient, boundary smoothness, and the rib information. Expand
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Robust and accurate iris segmentation in very noisy iris images
TLDR
We propose a limbic boundary localization algorithm that combines K-Means clustering based on the gray-level co-occurrence histogram and an improved Hough transform, and, in possible failures, a complementary method that uses skin information. Expand
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