Sentence examples for matching of objects from inspiring English sources

And perhaps the finding and matching of objects mimics tasks our brains are good at, but don't get to do very much any more, like searching for ripe fruit in tangled thickets, or picking stones out of dried lentils.

However, when objects were inverted, or upright but shown in a three-quarter view, the matching of objects and faces was equally sensitive to SF changes.

According to Mark Bould, the author of the Routledge Companion To Science Fiction, it's this mixing and matching of objects from different time periods that marks out the most credible big-screen futures, Blade Runner and Back to the Future Part II among them.

Like "Sesame Street," Building Blocks has children play creative counting games; but it also focuses on other number skills, including cardinality (how many objects are in a set) and one-to-one correspondence (matching groups of objects, like cups and saucers).

To address this limitation, we placed constraints on each matching supporter but not on the image as a whole, allowing the matching of deformable objects.

In particular, when using nearest neighbor matching of segmented objects, the occurrence of only a few turnovers can trigger a series of many tracking failures.

The algorithm matches 98.8% of objects to within 15 pixels.

For each of our 60 healthy right- and left-handed individuals, we computed a threshold-free LI (Nagata et al. 2001) on 2 different contrasts that tested for 1) semantic matching on words relative to perceptual matching on symbols and 2) semantic matching on pictures of objects relative to perceptual matching on pictures of nonobjects.

The huge variation in the shape, size and texture of the objects we must daily interact in a skillful and precise manner demands that this transformation provides a highly specific and selective matching of the object's properties to the motor commands for grasp and manipulation.

Over the experiment, there were 4 conditions (see Fig. 2 of Josse et al. 2008): 1) semantic matching on written object names presented in 16 blocks, 2) semantic matching on pictures of objects presented in 16 blocks, 3) perceptual matching on unfamiliar Greek symbols presented in 8 blocks, and 4) perceptual matching on unfamiliar pictures of nonobjects presented in 8 blocks.

We apply the theory to the task of recognizing cars observed by cameras at widely separated sites in a freeway network, with new heuristics to handle the inevitable complexity of matching large numbers of objects and with online learning of appearance probability models.