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There has recently been increasing interest in using advanced computer vision techniques for automatic plant identification. Most of the approaches proposed are based on an analysis of leaf characteristics. Nevertheless, two aspects have still not been well exploited: (1) domain-specific or botanical knowledge (2) the extraction of meaningful and relevant(More)
Macrophages, which are CD4 and CCR5 positive, can sustain HIV-1 replication for long periods of time. Thus, these cells play critical roles in the transmission, dissemination and persistence of viral infection. Of note, current antiviral therapies do not target macrophages efficiently. Previously, it was demonstrated that interactions between CCR5 and gp120(More)
Automatic plant identification is a relatively new research area in computer vision that has increasingly attracted high interest as a promising solution for the development of many botanical industries and for the success of biodiversity conservation. Most of the approaches proposed are based on the analysis of morphological properties of leaves. They have(More)
Structuring the search space based on domain-specific vocabulary (or concepts) is capital for enhanced image retrieval. In this paper, we study the opportunities and the impact of exploiting such a strategy in a particular problem which is the leaf species identification. We believe that such a solution is promising to reduce the effect of the high(More)
Leaves of plants can be classified as being either simple or compound according to their shapes. Compound leaves can be seen as a collection of simple leaf-like structures called leaflets. However, most computer vision-based approaches describe these two leaf categories similarly. In this paper, we propose a new description and identification method for(More)