Information maximization in face processing
نویسندگان
چکیده
منابع مشابه
Information maximization in face processing
This perspective paper explores principles of unsupervised learning and how they relate to face recognition. Dependency coding and information maximization appear to be central principles in neural coding early in the visual system. These principles may be relevant to how we think about higher visual processes such as face recognition as well. The paper first reviews examples of dependency lear...
متن کاملFace Modeling by Information Maximization
A number of current face recognition algorithms use face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and represent faces as a linear combination of those images. Principal component analysis (PCA) is a popular example of such methods. The basis images found by PCA depend only on pair-wise relationships between pixels in the image...
متن کاملUtility maximization and bounds on human information processing.
Utility maximization is a key element of a number of theoretical approaches to explaining human behavior. Among these approaches are rational analysis, ideal observer theory, and signal detection theory. While some examples of these approaches define the utility maximization problem with little reference to the bounds imposed by the organism, others start with, and emphasize approaches in which...
متن کاملInformation Maximization in Single Neurons
Information from the senses must be compressed into the limited range of firing rates generated by spiking nerve cells. Optimal compression uses all firing rates equally often, implying that the nerve cell's response matches the statistics of naturally occurring stimuli. Since changing the voltage-dependent ionic conductances in the cell membrane alters the flow of information, an unsupervised,...
متن کاملStochastic Fuzzy Discrimination Information Measure Cost Function in Image Processing
A new cost function based on stochastic fuzzy discrimination information measure is introduced in this paper. Focusing on their significant parts, this cost function is used to find the optimal value of threshold for denoising image. It is, in fact, an extension of fuzzy entropy cost function by the present author. Multivariable normal distribution is used for creating focus on significant part...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neurocomputing
سال: 2007
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2006.02.025