most citedEvaluating Four FPGA-accelerated Space Use Cases based on Neural Network Algorithms for On-board Inference

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eess.IV2023

The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data

Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle +35

Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Publ…

eess.IV2020

Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging

Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky +37

Our motivating application is a real-world problem: COVID-19 classification from CT imaging, for which we present an explainable Deep Learning approach based on a semi-supervised c…