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09/15/2023
Performance Metrics for Probabilistic Ordinal Classifiers
Ordinal classification models assign higher penalties to predictions fur...
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03/02/2023
Multi-Head Multi-Loss Model Calibration
Delivering meaningful uncertainty estimates is essential for a successfu...
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11/28/2022
Class Adaptive Network Calibration
Recent studies have revealed that, beyond conventional accuracy, calibra...
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09/13/2022
On the Optimal Combination of Cross-Entropy and Soft Dice Losses for Lesion Segmentation with Out-of-Distribution Robustness
We study the impact of different loss functions on lesion segmentation f...
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01/02/2022
FUSeg: The Foot Ulcer Segmentation Challenge
Acute and chronic wounds with varying etiologies burden the healthcare s...
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11/30/2021
The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration
In spite of the dominant performances of deep neural networks, recent wo...
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11/12/2021
Convolutional Nets Versus Vision Transformers for Diabetic Foot Ulcer Classification
This paper compares well-established Convolutional Neural Networks (CNNs...
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10/05/2021
Double Encoder-Decoder Networks for Gastrointestinal Polyp Segmentation
Polyps represent an early sign of the development of Colorectal Cancer. ...
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09/20/2021
Balanced-MixUp for Highly Imbalanced Medical Image Classification
Highly imbalanced datasets are ubiquitous in medical image classificatio...
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04/18/2021
The hidden label-marginal biases of segmentation losses
Most segmentation losses are arguably variants of the Cross-Entropy (CE)...
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10/01/2020
Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images
Assessing the degree of disease severity in biomedical images is a task ...
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09/03/2020
The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models
The segmentation of the retinal vasculature from eye fundus images repre...
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07/27/2020
Learned Pre-Processing for Automatic Diabetic Retinopathy Detection on Eye Fundus Images
Diabetic Retinopathy is the leading cause of blindness in the working-ag...
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08/28/2019
Self-supervised blur detection from synthetically blurred scenes
Blur detection aims at segmenting the blurred areas of a given image. Re...
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08/28/2019
O-MedAL: Online Active Deep Learning for Medical Image Analysis
Active Learning methods create an optimized and labeled training set fro...
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10/09/2018
UOLO - automatic object detection and segmentation in biomedical images
We propose UOLO, a novel framework for the simultaneous detection and se...
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09/25/2018
MedAL: Deep Active Learning Sampling Method for Medical Image Analysis
Deep learning models have been successfully used in medical image analys...
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12/07/2017
On the Duality Between Retinex and Image Dehazing
Image dehazing deals with the removal of undesired loss of visibility in...
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03/10/2017
Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis
Dermoscopic skin images are often obtained with different imaging device...
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01/31/2017