This paper presents a framework for using high-level visual information to enhance the performance of automatic color constancy algorithms. The approach is based on recognizing spe...
Esa Rahtu, Jarno Nikkanen, Juho Kannala, Leena Lep...
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
This paper gives the SNAP and SPAN ontologies relating to recognizing variable vista spatial environments, namely, SNAPVis and SPANVis. It proposes that recognizing spatial environ...
This paper outlines a symbolic computational theory for recognizing variable spatial environments-The Theory of Cognitive Prism, (Dong 2005). This theory defines distance and orie...
Human beings have the ability to learn to recognize a new visual category based on only one or few training examples. Part of this ability might come from the use of knowledge fro...