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07/27/2023
Text-guided Foundation Model Adaptation for Pathological Image Classification
The recent surge of foundation models in computer vision and natural lan...
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07/22/2023
Pathology-and-genomics Multimodal Transformer for Survival Outcome Prediction
Survival outcome assessment is challenging and inherently associated wit...
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07/10/2023
AmadeusGPT: a natural language interface for interactive animal behavioral analysis
The process of quantifying and analyzing animal behavior involves transl...
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06/13/2023
Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity
Frequent interactions between individuals are a fundamental challenge fo...
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06/04/2023
Training Like a Medical Resident: Universal Medical Image Segmentation via Context Prior Learning
A major enduring focus of clinical workflows is disease analytics and di...
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03/21/2022
TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers
Combining information from multi-view images is crucial to improve the p...
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02/28/2022
A Multi-scale Transformer for Medical Image Segmentation: Architectures, Model Efficiency, and Benchmarks
Transformers have emerged to be successful in a number of natural langua...
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02/17/2022
Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications
Image-based characterization and disease understanding involve integrati...
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07/02/2021
UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
Transformer architecture has emerged to be successful in a number of nat...
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05/31/2021
Low-Dose CT Denoising Using a Structure-Preserving Kernel Prediction Network
Low-dose CT has been a key diagnostic imaging modality to reduce the pot...
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03/30/2021
Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training
Data augmentation has proved extremely useful by increasing training dat...
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11/28/2019
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation
Existing domain adaptation methods aim at learning features that can be ...
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11/14/2016
