Unlike fine-grained objects, these components typically encompass business functionality and need to be aware of the underlying business processes.
Objects may be familiar ones like hypertext, text, graphics, or unknown, often coarser-grained objects whose content and methods are supplied by other cooperating servers.
A description of the data and methods necessary for FEA of NL dynamics is used to explain the motivation for, practice of, and benefits from employing shallow class hierarchies of co-operating, fine-grained objects, as opposed to the traditional choice of deep class hierarchies of specialized, coarse-grained objects.
Fine-Grained Object Category Decoding Using fMRI in Human Visual Cortex.
Extensive experiments on multiple benchmarks demonstrate that the proposed model consistently performs better than conventional convolutional networks on classifying fine-grained object classes in low-resolution images.
This is in line with the idea that successful categorization of highly similar objects is mediated by learning fine-grained object features indicative of category membership.
With respect to knowledge of musical objects, superordinate knowledge about musical style (eras, composers) and note values (absolute pitch) is less vulnerable than fine-grained, object-specific knowledge about particular compositions.
(Some philosophers think that propositions are too coarse-grained as objects of belief, while sentences are too fine-grained. They take the objects of belief to be structured propositions.
The eclectic approach is illustrated by reporting experiences from a case study of identifying coarse-grained, persistent objects to be used in the migration of a COBOL system to a distributed component system.
The same holds for an assembled table, which forms an object aggregate at a finer grained level, but due to physical junctions (e.g. screws, nails, clinches, riveting bolts, welds, etc)., which hold the construction together, at the same time it also constitutes a bona fide piece of furniture at a coarser granularity.
