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07/19/2023
Improved Distribution Matching for Dataset Condensation
Dataset Condensation aims to condense a large dataset into a smaller one...
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06/30/2023
Exploration and Exploitation of Unlabeled Data for Open-Set Semi-Supervised Learning
In this paper, we address a complex but practical scenario in semi-super...
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06/01/2023
A Transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics
During the diagnostic process, clinicians leverage multimodal informatio...
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04/04/2023
EGC: Image Generation and Classification via a Single Energy-Based Model
Learning image classification and image generation using the same set of...
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04/04/2023
Multi-Level Contrastive Learning for Dense Prediction Task
In this work, we present Multi-Level Contrastive Learning for Dense Pred...
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01/30/2023
Advancing Radiograph Representation Learning with Masked Record Modeling
Modern studies in radiograph representation learning rely on either self...
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01/30/2023
Protein Representation Learning via Knowledge Enhanced Primary Structure Modeling
Protein representation learning has primarily benefited from the remarka...
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01/12/2023
Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation
Biomedical image segmentation plays a significant role in computer-aided...
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01/12/2023
Adaptive Context Selection for Polyp Segmentation
Accurate polyp segmentation is of great significance for the diagnosis a...
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01/11/2023
GraVIS: Grouping Augmented Views from Independent Sources for Dermatology Analysis
Self-supervised representation learning has been extremely successful in...
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01/06/2023
Graph Convolution Based Cross-Network Multi-Scale Feature Fusion for Deep Vessel Segmentation
Vessel segmentation is widely used to help with vascular disease diagnos...
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12/02/2022
Geometry-Aware Network for Domain Adaptive Semantic Segmentation
Measuring and alleviating the discrepancies between the synthetic (sourc...
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11/28/2022
RankDNN: Learning to Rank for Few-shot Learning
This paper introduces a new few-shot learning pipeline that casts releva...
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10/27/2022
UNet-2022: Exploring Dynamics in Non-isomorphic Architecture
Recent medical image segmentation models are mostly hybrid, which integr...
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10/14/2022
Mix and Reason: Reasoning over Semantic Topology with Data Mixing for Domain Generalization
Domain generalization (DG) enables generalizing a learning machine from ...
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08/19/2022
Diagnose Like a Radiologist: Hybrid Neuro-Probabilistic Reasoning for Attribute-Based Medical Image Diagnosis
During clinical practice, radiologists often use attributes, e.g. morpho...
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08/05/2022
Neighborhood Collective Estimation for Noisy Label Identification and Correction
Learning with noisy labels (LNL) aims at designing strategies to improve...
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07/31/2022
One-Shot Medical Landmark Localization by Edge-Guided Transform and Noisy Landmark Refinement
As an important upstream task for many medical applications, supervised ...
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07/29/2022
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels
Deep models trained with noisy labels are prone to over-fitting and stru...
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07/01/2022
Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance
Although deep learning algorithms have been intensively developed for co...
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06/06/2022
Relation Matters: Foreground-aware Graph-based Relational Reasoning for Domain Adaptive Object Detection
Domain Adaptive Object Detection (DAOD) focuses on improving the general...
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04/21/2022
Domain Invariant Model with Graph Convolutional Network for Mammogram Classification
Due to its safety-critical property, the image-based diagnosis is desire...
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03/29/2022
Harmonizing Pathological and Normal Pixels for Pseudo-healthy Synthesis
Synthesizing a subject-specific pathology-free image from a pathological...
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03/24/2022
Compound Domain Generalization via Meta-Knowledge Encoding
Domain generalization (DG) aims to improve the generalization performanc...
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03/23/2022
Scale-Equivalent Distillation for Semi-Supervised Object Detection
Recent Semi-Supervised Object Detection (SS-OD) methods are mainly based...
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03/17/2022
Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning
This paper presents new hierarchically cascaded transformers that can im...
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02/22/2022
PointMatch: A Consistency Training Framework for Weakly SupervisedSemantic Segmentation of 3D Point Clouds
Semantic segmentation of point cloud usually relies on dense annotation ...
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01/31/2022
BOAT: Bilateral Local Attention Vision Transformer
Vision Transformers achieved outstanding performance in many computer vi...
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01/25/2022
Real-time automatic polyp detection in colonoscopy using feature enhancement module and spatiotemporal similarity correlation unit
Automatic detection of polyps is challenging because different polyps va...
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01/07/2022
Cross-Modality Deep Feature Learning for Brain Tumor Segmentation
Recent advances in machine learning and prevalence of digital medical im...
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01/05/2022
Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-training
The difficulties in both data acquisition and annotation substantially r...
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11/04/2021
Generalized Radiograph Representation Learning via Cross-supervision between Images and Free-text Radiology Reports
Pre-training lays the foundation for recent successes in radiograph anal...
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10/11/2021
Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-Contrast CT Images
Quantitative estimation of the acute ischemic infarct is crucial to impr...
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10/08/2021
Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition
Context, as referred to situational factors related to the object of int...
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09/07/2021
nnFormer: Interleaved Transformer for Volumetric Segmentation
Transformers, the default model of choices in natural language processin...
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08/24/2021
Identification of Pediatric Respiratory Diseases Using Fine-grained Diagnosis System
Respiratory diseases, including asthma, bronchitis, pneumonia, and upper...
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08/18/2021
ME-PCN: Point Completion Conditioned on Mask Emptiness
Point completion refers to completing the missing geometries of an objec...
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08/16/2021
CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
Brain lesion segmentation provides a valuable tool for clinical diagnosi...
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08/02/2021
GraphFPN: Graph Feature Pyramid Network for Object Detection
Feature pyramids have been proven powerful in image understanding tasks ...
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07/31/2021
Multi-scale Matching Networks for Semantic Correspondence
Deep features have been proven powerful in building accurate dense seman...
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06/13/2021
Domain Generalization on Medical Imaging Classification using Episodic Training with Task Augmentation
Medical imaging datasets usually exhibit domain shift due to the variati...
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05/31/2021
Hierarchical Deep Network with Uncertainty-aware Semi-supervised Learning for Vessel Segmentation
The analysis of organ vessels is essential for computer-aided diagnosis ...
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05/21/2021
Act Like a Radiologist: Towards Reliable Multi-view Correspondence Reasoning for Mammogram Mass Detection
Mammogram mass detection is crucial for diagnosing and preventing the br...
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05/01/2021
Cross-Modal Self-Attention with Multi-Task Pre-Training for Medical Visual Question Answering
Due to the severe lack of labeled data, existing methods of medical visu...
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04/21/2021
A Structure-Aware Relation Network for Thoracic Diseases Detection and Segmentation
Instance level detection and segmentation of thoracic diseases or abnorm...
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04/19/2021
Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation
In semi-supervised domain adaptation, a few labeled samples per class in...
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03/30/2021
Generalized Organ Segmentation by Imitating One-shot Reasoning using Anatomical Correlation
Learning by imitation is one of the most significant abilities of human ...
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03/25/2021
I^3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors
Recent works on two-stage cross-domain detection have widely explored th...
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03/24/2021
Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization
Unsupervised domain adaptation (UDA) in semantic segmentation is a funda...
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03/24/2021
