
Towards Robust Medical Image Segmentation on SmallScale Data with Incomplete Labels
The datadriven nature of deep learning models for semantic segmentation...
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Weight Encode Reconstruction Network for Computed Tomography in a SemiCaseWise and LearningBased Way
Classic algebraic reconstruction technology (ART) for computed tomograph...
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Improving Lesion Segmentation for Diabetic Retinopathy using Adversarial Learning
Diabetic Retinopathy (DR) is a leading cause of blindness in working age...
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Inference on the History of a Randomly Growing Tree
The spread of infectious disease in a human community or the proliferati...
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SiamSNN: Spikebased Siamese Network for EnergyEfficient and Realtime Object Tracking
Although deep neural networks (DNNs) have achieved fantastic success in ...
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Meta3D: SingleView 3D Object Reconstruction from Shape Priors in Memory
3D shape reconstruction from a singleview RGB image is an illposed pro...
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AITom: Opensource AI platform for cryoelectron Tomography data analysis
Cryoelectron tomography (cryoET) is an emerging technology for the 3D ...
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A Deep Learning System That Generates Quantitative CT Reports for Diagnosing Pulmonary Tuberculosis
We developed a deep learning modelbased system to automatically generat...
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Structured Modeling of Joint Deep Feature and Prediction Refinement for Salient Object Detection
Recent saliency models extensively explore to incorporate multiscale co...
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Visual Analytics of Student Learning Behaviors on K12 Mathematics Elearning Platforms
With increasing popularity in online learning, a surge of Elearning pla...
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MURS: Practical and Robust Privacy Amplification with MultiParty Differential Privacy
When collecting information, local differential privacy (LDP) alleviates...
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Practical and Robust Privacy Amplification with MultiParty Differential Privacy
When collecting information, local differential privacy (LDP) alleviates...
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Deep LearningBased Strategy for Macromolecules Classification with Imbalanced Data from Cellular Electron Cryotomography
Deep learning model trained by imbalanced data may not work satisfactori...
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Highdimensional nonparametric density estimation via symmetry and shape constraints
We tackle the problem of highdimensional nonparametric density estimati...
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Dual Pattern Learning Networks by Empirical Dual Prediction Risk Minimization
Motivated by the observation that humans can learn patterns from two giv...
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RespondCAM: Analyzing Deep Models for 3D Imaging Data by Visualizations
The convolutional neural network (CNN) has become a powerful tool for va...
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Multitask Learning for Macromolecule Classification, Segmentation and Coarse Structural Recovery in CryoTomography
Cellular Electron CryoTomography (CECT) is a powerful 3D imaging tool f...
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Imagederived generative modeling of pseudomacromolecular structures  towards the statistical assessment of Electron CryoTomography template matching
Cellular Electron CryoTomography (CECT) is a 3D imaging technique that c...
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An integration of fast alignment and maximumlikelihood methods for electron subtomogram averaging and classification
Motivation: Cellular Electron CryoTomography (CECT) is an emerging 3D im...
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A Telecom Perspective on the Internet of Drones: From LTEAdvanced to 5G
Drones are driving numerous and evolving use cases, and creating transfo...
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AAANE: Attentionbased Adversarial Autoencoder for Multiscale Network Embedding
Network embedding represents nodes in a continuous vector space and pres...
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Deep learning based supervised semantic segmentation of Electron CryoSubtomograms
Cellular Electron CryoTomography (CECT) is a powerful imaging technique...
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Model compression for faster structural separation of macromolecules captured by Cellular Electron CryoTomography
Electron CryoTomography (ECT) enables 3D visualization of macromolecule...
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Feature Decomposition Based Saliency Detection in Electron CryoTomograms
Electron CryoTomography (ECT) allows 3D visualization of subcellular st...
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Performance Optimization and Parallelization of a Parabolic Equation Solver in Computational Ocean Acoustics on Modern Manycore Computer
As one of opensource codes widely used in computational ocean acoustics...
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A convolutional autoencoder approach for mining features in cellular electron cryotomograms and weakly supervised coarse segmentation
Cellular electron cryotomography enables the 3D visualization of cellul...
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Experience enrichment based task independent reward model
For most reinforcement learning approaches, the learning is performed by...
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Learning Multilevel Deep Representations for Image Emotion Classification
In this paper, we propose a new deep network that learns multilevel dee...
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Modelling Temporal Information Using Discrete Fourier Transform for Recognizing Emotions in Usergenerated Videos
With the widespread of usergenerated Internet videos, emotion recogniti...
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Integrative analysis of gene expression and phenotype data
The linking genotype to phenotype is the fundamental aim of modern genet...
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Global Gene Expression Analysis Using Machine Learning Methods
Microarray is a technology to quantitatively monitor the expression of l...
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Gene selection for cancer classification using a hybrid of univariate and multivariate feature selection methods
Various approaches to gene selection for cancer classification based on ...
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Automatic tracking of protein vesicles
With the advance of fluorescence imaging technologies, recently cell bio...
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Faithful Variable Screening for HighDimensional Convex Regression
We study the problem of variable selection in convex nonparametric regre...
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Efficient Hybrid Inline and Outofline Deduplication for Backup Storage
Backup storage systems often remove redundancy across backups via inline...
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Connectivitypreserving Geometry Images
We propose connectivitypreserving geometry images (CGIMs), which map a ...
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Conditional Sparse Coding and Grouped Multivariate Regression
We study the problem of multivariate regression where the data are natur...
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Efficient Active Algorithms for Hierarchical Clustering
Advances in sensing technologies and the growth of the internet have res...
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Highdimensional covariance estimation based on Gaussian graphical models
Undirected graphs are often used to describe high dimensional distributi...
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Forest Density Estimation
We study graph estimation and density estimation in high dimensions, usi...
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Min Xu
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Assistant Research Professor and Trainning Faculty at Carnegie Mellon University