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Vision Transformers for Analyzing High-Resolution Pathology Images

Master Thesis Transformers are powerful models that can capture long-range dependencies between data using an attention mechanism. However, applying transformers to medical problems poses challenges due to the high-resolution and complexity of pathology images, as well as the scarcity and noise of labels. In this…

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Towards Robust and Adaptable Diagnosis of Pneumonia from Chest X-ray Data

Visual Intelligence, 90/100, 2021 Artificial intelligence (AI) researchers and radiologists have recently reported AI systems that accurately diagnose pneumonia from a chest X-Ray images using deep neural networks when trained on a sufficient large and homogeneous amount of labelled images. However, the robustness and adaptability…

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Detecting Rooftop Area for installing PV modules with Deep Learning

Machine Learning, 100/100, 2021 Won the 2nd place for best project presentation, presented at the CISBAT 2021 and published in the Journal of Physics. With Prof. Castello, we worked on Deep-learning for the detection of available for solar panel installation from satellite images. This computer…

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A photo from Raphaël’s collection