John Jacobson

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Glycoprotein hormones (GPHs) comprise a group of signaling molecules critical for major metabolic and reproductive functions. In vertebrates they include chorionic gonadotropin, LH, FSH, and TSH. The active hormones are characterized by heterodimerization between a common α and hormone-specific β subunit, which activate leucine-rich repeat-containing G(More)
Brightness--the perception of an object's luminance--arises from complex and poorly understood interactions at several levels of processing. It is well known that the brightness of an object depends on its spatial context, which can include perceptual organization, scene interpretation, three-dimensional interpretation, shadows, and other high-level(More)
Hyperspectral imaging systems for daylight operation measure and analyze reflected and scattered radiation in p-spectral channels covering the reflective infrared region 0.4-2.5 microm. Consequently, the p-dimensional joint distribution of background clutter is required to design and evaluate optimum hyperspectral imaging processors. In this paper, we(More)
The identification, assessment, and management of hearing impairment in the pediatric population can be a challenging endeavor. Nevertheless, newer technology, improved techniques, and the cooperative efforts of various professional organizations and their constituencies have made significant strides toward achieving this goal. As more precise objective(More)
(i) a new metric to assess urban density (UD) from multi-spectral and LiDAR data, (ii) simulation-based techniques to jointly use SAR and LiDAR data for image interpretation and change detection , and (iii) radiosity methods to improve surface reflectance retrievals of optical data in complex illumination environments. In particular, they demonstrate the(More)
The main objective of this paper is to discuss the effects of signature mismatch on hyperspectral target detection algorithms. The main causes of mismatch are atmospheric propagation, intrinsic spectral variability, sensor noise, and sensor artifacts. We provide a theoretical analysis that shows the effects of mismatch on adaptive detection algorithms,(More)
Most detection algorithms for hyperspectral imaging applications assume a target with a perfectly known spectral signature. In practice, the target signature is either imperfectly measured (target mismatch) and/or it exhibits spectral variability. The objective of this paper is to introduce a robust matched filter that takes the uncertainty and/or(More)
We suggest that a simple model (Fig S1) may explain our results: (1) the system commits to brightness values of objects in the scene, (2) these commitments hold even while neural responses adapt, (3) V1 neural activity encoding the brightness of two objects is compared, and the difference of activities produces a difference between assigned labels. Since(More)