The fundamental idea of our novel approach is the geometry-aware object segmentation, by which an arbitrarily complicated surface model can be decomposed into a group of disjoint components that comprise branches, handles, and base patches.
Through experimental results on a bird image dataset, we show the effectiveness of the method for scale-aware object detection.
The proposed method was experimentally evaluated with a bird dataset especially constructed for ecological investigations around wind farms, showing that combining deep features from a detector and semantic segmentation is effective for scale-aware object detection.
We become consciously aware of objects and events by virtue of paying attention to them.
Conceptions are ways of being aware of objects.
While there is debate over the precise sense in which, for Reid, we are directly aware of objects, this much seems clear: whatever the sense of "direct" is in which the subscribers to the representational theory take us to be directly aware of ideas, it is in that sense that Reid takes us to be directly aware of real objects.
However, when we come to be aware of objects through our senses, we do so by utilizing something like a language embedded in our constitutions: our sensations function like a language that nature has constructed.
Intertwined with Reid's arguments that we can be immediately aware of objects through their relational properties such as their apparent magnitudes are Reid's arguments regarding the distinction between primary and secondary qualities.
With Amazon's newly opened up visual recognition technology, developers will not only be able to make their existing apps smarter and more aware of objects out in the real world, they can potentially develop new kinds of applications entirely.
They aren't particularly aware of objects to know they have disappeared from sight.
