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09/12/2023
Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation
Single-modality medical images generally do not contain enough informati...
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09/12/2023
Medical Image Segmentation with Belief Function Theory and Deep Learning
Deep learning has shown promising contributions in medical image segment...
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06/23/2022
Evidence fusion with contextual discounting for multi-modality medical image segmentation
As information sources are usually imperfect, it is necessary to take in...
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05/03/2022
Application of belief functions to medical image segmentation: A review
Belief function theory, a formal framework for uncertainty analysis and ...
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04/20/2022
Broad Recommender System: An Efficient Nonlinear Collaborative Filtering Approach
Recently, Deep Neural Networks (DNNs) have been widely introduced into C...
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03/12/2022
G^3SR: Global Graph Guided Session-based Recommendation
Session-based recommendation tries to make use of anonymous session data...
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01/31/2022
Lymphoma segmentation from 3D PET-CT images using a deep evidential network
An automatic evidential segmentation method based on Dempster-Shafer the...
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08/11/2021
Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation
Lymphoma detection and segmentation from whole-body Positron Emission To...
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04/27/2021
Evidential segmentation of 3D PET/CT images
PET and CT are two modalities widely used in medical image analysis. Acc...
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03/10/2021
BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism
Collaborative Filtering (CF) based recommendation methods have been wide...
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01/29/2021
Belief function-based semi-supervised learning for brain tumor segmentation
Precise segmentation of a lesion area is important for optimizing its tr...
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01/18/2021
Covid-19 classification with deep neural network and belief functions
Computed tomography (CT) image provides useful information for radiologi...
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12/15/2020
Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative Framework
Since the label collecting is prohibitive and time-consuming, unsupervis...
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01/15/2019
DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System
In general, recommendation can be viewed as a matching problem, i.e., ma...
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11/06/2018
DIAG-NRE: A Deep Pattern Diagnosis Framework for Distant Supervision Neural Relation Extraction
Modern neural network models have achieved the state-of-the-art performa...
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10/16/2018
On Finding Dense Subgraphs in Bipartite Graphs: Linear Algorithms with Applications to Fraud Detection
Detecting dense subgraphs from large graphs is a core component in many ...
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10/15/2018
Bounding Entities within Dense Subtensors
Group-based fraud detection is a promising methodology to catch frauds o...
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05/25/2018
BadLink: Combining Graph and Information-Theoretical Features for Online Fraud Group Detection
Frauds severely hurt many kinds of Internet businesses. Group-based frau...
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03/15/2012
Online Semi-Supervised Learning on Quantized Graphs
In this paper, we tackle the problem of online semi-supervised learning ...
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01/28/2011
An Analysis of the Convergence of Graph Laplacians
Existing approaches to analyzing the asymptotics of graph Laplacians typ...
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09/30/2010
