Visual Turing Test datasets and evaluation metrics so the performances can be compared. This led to the emergence of challenges like the Pascal VOC challenge and the ImageNet challenge. The availability of standard evaluation metrics and the open challenges gave directions to the research. Better algorithms were introduced for specific tasks like object detection and classification. Visual Turing Test aims to give a new direction to the computer vision research which would lead to the introduction of systems that will be one step closer to understanding images the way humans do. A large number of datasets have been annotated and generalised to benchmark
Turing degree same level of unsolvability; each Turing degree is a collection of Turing equivalent sets, so that two sets are in different Turing degrees exactly when they are not Turing equivalent. Furthermore, the Turing degrees are partially ordered so that if the Turing degree of a set "X" is less than the Turing degree of a set "Y" then any (noncomputable) procedure that correctly decides whether numbers are in "Y" can be effectively converted to a procedure that correctly decides whether numbers are in "X". It is in this sense that the Turing degree of a set corresponds to its level