Asma Rejeb Sfar

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We study fine-grained categorization, the task of distinguishing among (sub)categories of the same generic object class (e.g., birds), focusing on determining botanical species (leaves and orchids) from scanned images. The strategy is to focus attention around several vantage points, which is the approach taken by botanists, but using features dedicated to(More)
We present a new hierarchical strategy for fine-grained categorization. Standard, fully automated systems report a single estimate of the category, or perhaps a ranked list, but have non-neglible error rates for most realistic scenarios, which limits their utility. Instead, we propose a semi-automated system which outputs a it confidence set (CS)—a(More)
Automatic retrieval tools are becoming increasingly important in botany and agriculture due to the growing interest in biodiversity and the ongoing shortage of skilled taxonomists. Our work is motivated by a botanical field scenario where the basic unit of observation is a plant. We describe a novel, image-based retrieval system for both educational and(More)
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