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Fully automated high-throughput and high-content experiments need reusable general modules, that can be combined in a flexible way to build the solution. Even though the biological objects or structures may not share any common features, the transformations that act on the structures (like rotations, translations or deformations) are nearly the same in every experiment. In the talk I will show general...
In this paper, we propose a novel multi-class graph boosting algorithm to recognize different visual objects. The proposed method treats subgraph as feature to construct base classifier, and utilizes popular error correcting output code scheme to solve multi-class problem. Both factors, base classifier and error-correcting coding matrix are considered simultaneously. And subgragphs, which are shareable...
Hyperspectral remote sensing, as a new remote sensing technology, provides a powerful measure to object identification and classification accurately due to its acuminous ability of spectrum detection. This paper addresses the problem of the classification of hyperspectral remote-sensing images, and studies a novel spectral matching method based on the popular Scale-invariant Feature Transform (SIFT)...
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