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We make an analogy between images and statistical mechanics systems. Pixel gray levels and the presence and orientation of edges are viewed as states of atoms or molecules in a lattice-like physical system. The assignment of an energy function in the physical system determines its Gibbs distribution. Because of the Gibbs distribution, Markov random field(More)
We explore a new approach to shape recognition based on a virtually innnite family of binary features (\queries") of the image data, designed to accommodate prior information about shape invariance and regularity. Each query corresponds to a spatial arrangement of several local topographic codes (\tags") which are in themselves too primitive and common to(More)
One popular method for the recovery of an ideal intensity image from corrupted or indirect measurements is regularization: minimize an objective function that enforces a roughness penalty in addition to coherence with the data. Linear estimates are relatively easy to compute but generally introduce systematic errors; for example, they are incapable of(More)
MOTIVATION Various studies have shown that cancer tissue samples can be successfully detected and classified by their gene expression patterns using machine learning approaches. One of the challenges in applying these techniques for classifying gene expression data is to extract accurate, readily interpretable rules providing biological insight as to how(More)
Traditional image retrieval methods require a " query image " to initiate a search for members of an image category. However, when the image database is unstructured, and when the category is semantic and resides only in the mind of the user, there is no obvious way to begin (the " page zero " problem). We propose a new mathematical framework for relevance(More)
We use a statistical framework for finding boundaries and for partitioning scenes into homogeneous regions. The model is a joint probability distribution for the array of pixel gray levels and an array of " labels. " In boundary finding, the labels are binary, zero, or one, representing the absence o r presence of boundary elements. In partitioning , the(More)
High-throughput technologies are widely used, for example to assay genetic variants, gene and protein expression, and epigenetic modifications. One often overlooked complication with such studies is batch effects, which occur because measurements are affected by laboratory conditions, reagent lots and personnel differences. This becomes a major problem when(More)
Most discriminative techniques for detecting instances from object categories in still images consist of looping over a partition of a pose space with dedicated binary classifiers. The efficiency of this strategy for a complex pose, i.e., for fine-grained descriptions, can be assessed by measuring the effect of sample size and pose resolution on accuracy(More)