"training object" is a correct and usable phrase in written English.
You can use it when talking about an object that is used for training or practicing a specific skill or task. Example: The new employees were given a training object to practice their handling and assembly techniques before working on the actual product.
For model learning, I present a framework for training object detectors using only one-bit image level annotations of object presence without any instance level annotations (i.e. bounding boxes).
These results resolve the confounding of training object and training task in Experiment 2 and, in addition to replicating our result, they rule out the alternative explanation that the present training effects are caused by general arousal or engagement with the game.
To overcome the need for large amount of labeled data for training object instance detectors we use active self-supervision provided by a robot traversing an environment.
We proposed a novel method for semi-automated selection of training objects in this heterogeneous landscape using extreme values of spectral indices (SIs) estimated from satellite data.
Those training objects with are called Support Vectors, because only they determine direction : (15).
This opening serves to bring in light, environmental or by a desk lamp (Fig. 2), as well as to be able to manually move training objects inside the box.
Choose a blue (or candy) split level igloo Choose wooden flooring Install 2 security cams and set a guard You'll need training objects these include shootout practice these are created by placing ninja dummies from the ninja party 2011.
The material comprised of the three actions pertaining to 12 of the 24 trained object nouns (four nouns per gender-like subclass), resulting in 36 actions in total.
Crucially, failure to test pure generalization prevents a robust assessment of what component of rat invariant recognition can be ascribed to a spontaneous, purely perceptual evaluation of visual similarity (i.e., to a true generalization process), and what component, instead, depends on learning arbitrary associative relations among trained object views.
It is an open question whether there is similar neural plasticity in AV integration of cross-modally trained objects.
The consensus is built using brainstorming technology, which combines multi-objective instances of machine learning algorithm, and the data fusion of different training objects representations, in order to boost the overall prediction accuracy of conserved short sequence motifs.
