Guillaume Lemaître

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This paper addresses the problem of automatic classification of Spectral Domain OCT (SD-OCT) data for automatic identification of patients with DME versus normal subjects. Optical Coherence Tomography (OCT) has been a valuable diagnostic tool for DME, which is among the most common causes of irreversible vision loss in individuals with diabetes. Here, a(More)
Endpoints or conference servers of current audio-conferencing solutions use all the audio frames they receive in order to mix them into one final aggregate stream. However, at each time-instant, some of this content may not be audible due to auditory masking. Hence, sending corresponding frames through the network leads to a loss of bandwidth, while(More)
BACKGROUND Spectral domain optical coherence tomography (OCT) (SD-OCT) is most widely imaging equipment used in ophthalmology to detect diabetic macular edema (DME). Indeed, it offers an accurate visualization of the morphology of the retina as well as the retina layers. METHODS The dataset used in this study has been acquired by the Singapore Eye(More)
In this work, pruning techniques for the AdaBoost clas-sifier are evaluated specially aimed for a continuous learning framework in sensors mining applications. To assess the methods, three pruning schemes are evaluated using standard machine-learning benchmark datasets, simulated drifting datasets and real cases. Early results obtained show that pruning(More)
HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt età la diffusion(More)
A natural scene image contains object categories which form ambiguous boundaries. Measuring this ambiguitywhile classifying an image, is a challenging task. A scene image belongs to multiple categories at a time which makes a task of classification multi label one. Binary classification fails to capture this ambiguity while classifying the scene image into(More)
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