Bert Vankeirsbilck

Dermatologist versus artificial intelligence confidence in dermoscopy diagnosis: Complementary information that may affect decision‐making

Pieter Van Molle, Sofie Mylle, Tim Verbelen, Cedric De Boom et autres

In dermatology, deep learning may be applied for skin lesion classification. However, for a given input image, a neural network only outputs a label, obtained using the class probabilities, which do not model uncertainty. Our group developed a novel method to quantify …

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The value of measuring uncertainty in neural networks in dermoscopy

Pieter Van Molle, Liève Brochez, Tim Verbelen, Cedric De Boom et autres

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Data-Efficient Sensor Upgrade Path Using Knowledge Distillation

Pieter Van Molle, Cedric De Boom, Tim Verbelen, Bert Vankeirsbilck et autres

Deep neural networks have achieved state-of-the-art performance in image classification. Due to this success, deep learning is now also being applied to other data modalities such as multispectral images, lidar and radar data. However, successfully training a deep neural network requires a …

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Leveraging the Bhattacharyya coefficient for uncertainty quantification in deep neural networks

Pieter Van Molle, Tim Verbelen, Bert Vankeirsbilck, Jonas De Vylder et autres

Abstract Modern deep learning models achieve state-of-the-art results for many tasks in computer vision, such as image classification and segmentation. However, its adoption into high-risk applications, e.g. automated medical diagnosis systems, happens at a slow pace. One of the main reasons for …

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Training binary neural networks with knowledge transfer

Sam Leroux, Bert Vankeirsbilck, Tim Verbelen, Pieter Simoens et autres

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Multi-fidelity deep neural networks for adaptive inference in the internet of multimedia things

Sam Leroux, Steven Bohez, Elias De Coninck, Pieter Van Molle et autres

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A study on confidence in classification of skin lesions by deep neural networks

Pieter Van Molle, Tim Verbelen, Bert Vankeirsbilck, Sofie Mylle et autres

Quantifying Uncertainty of Deep Neural Networks in Skin Lesion Classification

Pieter Van Molle, Tim Verbelen, Cedric De Boom, Bert Vankeirsbilck et autres

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Assessing uncertainty for computer assisted skin lesion diagnosis

Pieter Van Molle, Tim Verbelen, Bert Vankeirsbilck, Sofie Mylle et autres

Visualizing Convolutional Neural Networks to Improve Decision Support\n for Skin Lesion Classification

Pieter Van Molle, Miguel De Strooper, Tim Verbelen, Bert Vankeirsbilck et autres

Because of their state-of-the-art performance in computer vision, CNNs are\nbecoming increasingly popular in a variety of fields, including medicine.\nHowever, as neural networks are black box function approximators, it is\ndifficult, if not impossible, for a medical expert to reason about their\noutput. This could …

DIANNE: a modular framework for designing, training and deploying deep neural networks on heterogeneous distributed infrastructure

Elias De Coninck, Steven Bohez, Sam Leroux, Tim Verbelen et autres

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Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification

Pieter Van Molle, Miguel De Strooper, Tim Verbelen, Bert Vankeirsbilck et autres

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