Portland, Oregon, United States
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Publications

  • Constrained Filter Optimization for Subsurface Landmine Detection,

    Proceedings of SPIE - The International Society for Optical Engineering

    Previous large-scale blind tests of anti-tank landmine detection utilizing the NIITEK ground penetrating radar indicated the potential for very high anti-tank landmine detection probabilities at very low false alarm rates for algorithms based on adaptive background cancellation schemes. Recent data collections under more heterogeneous multi-layered road-scenarios seem to indicate that although adaptive solutions to background cancellation are effective, the adaptive solutions to background…

    Previous large-scale blind tests of anti-tank landmine detection utilizing the NIITEK ground penetrating radar indicated the potential for very high anti-tank landmine detection probabilities at very low false alarm rates for algorithms based on adaptive background cancellation schemes. Recent data collections under more heterogeneous multi-layered road-scenarios seem to indicate that although adaptive solutions to background cancellation are effective, the adaptive solutions to background cancellation under different road conditions can differ significantly, and misapplication of these adaptive solutions can reduce landmine detection performance in terms of PD/FAR. In this work we present a framework for the constrained optimization of background-estimation filters that specifically seeks to optimize PD/FAR performance as measured by the area under the ROC curve between two FARs. We also consider the application of genetic algorithms to the problem of filter optimization for landmine detection. Results indicate robust results for both static and adaptive background cancellation schemes, and possible real-world advantages and disadvantages of static and adaptive approaches are discussed.

  • Image Processing Using One Dimensional Processor Arrays

    Proceedings of the IEEE

    The first half of this paper presents the design rationale for CNAPS, a specialized one-dimensional (1-D) processor array developed by Adaptive Solutions Inc. In this context, we discuss the problem of Amdahl's law which severely constrains special-purpose architectures. We also discuss specific architectural decisions such as the kind of parallelism, the computational precision of the processors, on-chip versus off-chip processor memory, and-most importantly-the interprocessor communication…

    The first half of this paper presents the design rationale for CNAPS, a specialized one-dimensional (1-D) processor array developed by Adaptive Solutions Inc. In this context, we discuss the problem of Amdahl's law which severely constrains special-purpose architectures. We also discuss specific architectural decisions such as the kind of parallelism, the computational precision of the processors, on-chip versus off-chip processor memory, and-most importantly-the interprocessor communication architecture. We argue that, for our particular set of applications, a 1-D architecture gives the best "bang for the buck", even when compared to the more traditional two-dimensional (2-D) architecture. The second half of this paper describes how several simple algorithms map to the CNAPS array. Our results show that the CNAPS 1-D array offers excellent performance over a range of IP algorithms. We also briefly look at the performance of CNAPS as a pattern recognition engine because many image processing and pattern recognition problems are intimately related.

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  • Differential Contributions of Circular and Elongated Spatial Filters to the Cafe Wall Illusion

    Biological Cybernetics

    The Café Wall illusion is induced in part by the spatial filtering properties of circular-symmetric receptive fields at the retina, and in part by cortical processes, presumably that have elongated receptive fields. Two experiments are reported that address these two contributions. The first shows a reversal effect that is consistent with brightness-induction and related theories. The second shows extinction of the effect in a manner predicted by recent observations of gating nonlinearity in…

    The Café Wall illusion is induced in part by the spatial filtering properties of circular-symmetric receptive fields at the retina, and in part by cortical processes, presumably that have elongated receptive fields. Two experiments are reported that address these two contributions. The first shows a reversal effect that is consistent with brightness-induction and related theories. The second shows extinction of the effect in a manner predicted by recent observations of gating nonlinearity in cortical cells.

Patents

  • Creating and verifying globally unique device-specific identifiers

    Issued US 8,751,815

    Methods, apparatuses, and articles for receiving, by a server, a plurality of identifiers associated with a client device are described herein. The server may also encrypt a plurality of encoding values associated with the plurality of identifiers using a first key of a key pair of the server, and generate a token uniquely identifying the client device, a body of the token including the encrypted plurality of encoding values. In other embodiments, the server may receive a token along with the…

    Methods, apparatuses, and articles for receiving, by a server, a plurality of identifiers associated with a client device are described herein. The server may also encrypt a plurality of encoding values associated with the plurality of identifiers using a first key of a key pair of the server, and generate a token uniquely identifying the client device, a body of the token including the encrypted plurality of encoding values. In other embodiments, the server may receive a token along with the plurality of identifiers. In such embodiments, the server may further verify the validity of the received token, including attempting to decrypt a body of the received token with a key associated with a second server, the second server having generated the received token, and, if decryption succeeds, comparing ones of the plurality of identifiers with second identifiers found in the decrypted body to check for inconsistencies.

    Other inventors
  • Visualizing Object Relationships

    Issued US 8,516,439

    Methods, apparatuses, and articles for enabling, by a computing device, provision of a visual manifestation of an object of interest and of one or more other objects related to the object of interest to a user of the computing device, are described herein. In various embodiments, the one or more other objects may be arranged in a manner conveying a degree of relationship, the visual manifestation further including a first indication of at least one exceptional relationship between any two…

    Methods, apparatuses, and articles for enabling, by a computing device, provision of a visual manifestation of an object of interest and of one or more other objects related to the object of interest to a user of the computing device, are described herein. In various embodiments, the one or more other objects may be arranged in a manner conveying a degree of relationship, the visual manifestation further including a first indication of at least one exceptional relationship between any two objects or a second indication of a security status of one of the objects. Further, the computing device may facilitate the user in interacting with the visual manifestation, including altering or expanding the visual manifestation in response to a user interaction.

  • Methods and apparatus for securely signing on to a website via a security website

    Issued US 7,526,796

    A method of providing a security website and verifying, by the security website, that a device of a user is authorized to access another website when the user attempts to access the another website via the security website.

    Other inventors
  • Method and Apparatus for Automatically Determining Salient Features for Object Classification

    Issued US 6,938,025

    A method and apparatus for automatically determining salient features for object classification is provided. In accordance with one embodiment, one or more unique features are extracted from a first content group of objects to form a first feature list, and one or more unique features are extracted from a second anti-content group of objects to form a second feature list. A ranked list of features is then created by applying statistical differentiation between unique features of the first…

    A method and apparatus for automatically determining salient features for object classification is provided. In accordance with one embodiment, one or more unique features are extracted from a first content group of objects to form a first feature list, and one or more unique features are extracted from a second anti-content group of objects to form a second feature list. A ranked list of features is then created by applying statistical differentiation between unique features of the first feature list and unique features of the second feature list. A set of salient features is then identified from the resulting ranked list of features.

  • A Very-Large-Scale Automatic Categorizer for Web Content

    Issued US 6,826,576

    A method and apparatus for efficiently classifying and categorizing data objects such as electronic text, graphics, and audio based documents within very-large-scale hierarchical classification trees is provided. In accordance with one embodiment of the invention, a first node of a plurality of nodes of a subject hierarchy is selected. Previously classified data objects corresponding to a selected first node of a subject hierarchy as well as any associated sub-nodes of the selected node are…

    A method and apparatus for efficiently classifying and categorizing data objects such as electronic text, graphics, and audio based documents within very-large-scale hierarchical classification trees is provided. In accordance with one embodiment of the invention, a first node of a plurality of nodes of a subject hierarchy is selected. Previously classified data objects corresponding to a selected first node of a subject hierarchy as well as any associated sub-nodes of the selected node are aggregated to form a content class of data objects. Similarly, data objects corresponding to sibling nodes of the selected node and any associated sub-nodes of the sibling nodes are then aggregated to form an anti-content class of data objects. Features are then extracted from each of the content class of data objects and the anti-content class of data objects to facilitate characterization of said previously classified data objects.

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