118,117 research outputs found

    The VEX-93 environment as a hybrid tool for developing knowledge systems with different problem solving techniques

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    The paper describes VEX-93 as a hybrid environment for developing knowledge-based and problem solver systems. It integrates methods and techniques from artificial intelligence, image and signal processing and data analysis, which can be mixed. Two hierarchical levels of reasoning contains an intelligent toolbox with one upper strategic inference engine and four lower ones containing specific reasoning models: truth-functional (rule-based), probabilistic (causal networks), fuzzy (rule-based) and case-based (frames). There are image/signal processing-analysis capabilities in the form of programming languages with more than one hundred primitive functions. User-made programs are embeddable within knowledge basis, allowing the combination of perception and reasoning. The data analyzer toolbox contains a collection of numerical classification, pattern recognition and ordination methods, with neural network tools and a data base query language at inference engines's disposal. VEX-93 is an open system able to communicate with external computer programs relevant to a particular application. Metaknowledge can be used for elaborate conclusions, and man-machine interaction includes, besides windows and graphical interfaces, acceptance of voice commands and production of speech output. The system was conceived for real-world applications in general domains, but an example of a concrete medical diagnostic support system at present under completion as a cuban-spanish project is mentioned. Present version of VEX-93 is a huge system composed by about one and half millions of lines of C code and runs in microcomputers under Windows 3.1.Postprint (published version

    Case-based reasoning combined with statistics for diagnostics and prognosis

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    Many approaches used for diagnostics today are based on a precise model. This excludes diagnostics of many complex types of machinery that cannot be modelled and simulated easily or without great effort. Our aim is to show that by including human experience it is possible to diagnose complex machinery when there is no or limited models or simulations available. This also enables diagnostics in a dynamic application where conditions change and new cases are often added. In fact every new solved case increases the diagnostic power of the system. We present a number of successful projects where we have used feature extraction together with case-based reasoning to diagnose faults in industrial robots, welding, cutting machinery and we also present our latest project for diagnosing transmissions by combining Case-Based Reasoning (CBR) with statistics. We view the fault diagnosis process as three consecutive steps. In the first step, sensor fault signals from machines and/or input from human operators are collected. Then, the second step consists of extracting relevant fault features. In the final diagnosis/prognosis step, status and faults are identified and classified. We view prognosis as a special case of diagnosis where the prognosis module predicts a stream of future features

    Context-aware Captions from Context-agnostic Supervision

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    We introduce an inference technique to produce discriminative context-aware image captions (captions that describe differences between images or visual concepts) using only generic context-agnostic training data (captions that describe a concept or an image in isolation). For example, given images and captions of "siamese cat" and "tiger cat", we generate language that describes the "siamese cat" in a way that distinguishes it from "tiger cat". Our key novelty is that we show how to do joint inference over a language model that is context-agnostic and a listener which distinguishes closely-related concepts. We first apply our technique to a justification task, namely to describe why an image contains a particular fine-grained category as opposed to another closely-related category of the CUB-200-2011 dataset. We then study discriminative image captioning to generate language that uniquely refers to one of two semantically-similar images in the COCO dataset. Evaluations with discriminative ground truth for justification and human studies for discriminative image captioning reveal that our approach outperforms baseline generative and speaker-listener approaches for discrimination.Comment: Accepted to CVPR 2017 (Spotlight

    CATV-The Continuing Copyright Controversy

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    Stay Tuned: Whether Cloud-Based Service Providers Can Have Their Copyrighted Cake and Eat It Too

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    Copyright owners have the exclusive right to perform their works publicly and the ability to license their work to others who want to share that right. Subsections 106(4) and (5) of the Copyright Act govern this exclusive public performance right, but neither subsection elaborates on what constitutes a performance made “to the public” versus one that remains private. This lack of clarity has made it difficult for courts to apply the Copyright Act consistently, especially in the face of changing technology. Companies like Aereo, Inc. and AereoKiller, Inc. developed novel ways to transmit content over the internet to be viewed instantly by their subscribers and declined to procure the licenses that would have been required if these transmissions were being made “to the public.” However, while these companies claimed that their activities were outside of the purview of § 106(4) and (5), their rivals, copyright owners, and the U.S. Supreme Court disagreed. Likening Aereo to a cable company for purposes of § 106(4) and (5), the Supreme Court determined that the company would need to pay for the material it streamed. Perhaps more problematic for Aereo (and other similar companies) is the fact that the Court declined to categorize Aereo as an actual cable company, such that it would qualify to pay compulsory licensing fees—the more affordable option given to cable companies under § 111—to copyright holders. This Comment shows that, while the Court correctly ruled that companies like Aereo and AereoKiller should pay for the content transmitted, its failure to address whether Aereo is a cable company could frustrate innovation to the detriment of the public. It suggests, therefore, that these companies should be required to pay for the content that they transmit in the same way that cable companies do until Congress develops another system

    Quick and energy-efficient Bayesian computing of binocular disparity using stochastic digital signals

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    Reconstruction of the tridimensional geometry of a visual scene using the binocular disparity information is an important issue in computer vision and mobile robotics, which can be formulated as a Bayesian inference problem. However, computation of the full disparity distribution with an advanced Bayesian model is usually an intractable problem, and proves computationally challenging even with a simple model. In this paper, we show how probabilistic hardware using distributed memory and alternate representation of data as stochastic bitstreams can solve that problem with high performance and energy efficiency. We put forward a way to express discrete probability distributions using stochastic data representations and perform Bayesian fusion using those representations, and show how that approach can be applied to diparity computation. We evaluate the system using a simulated stochastic implementation and discuss possible hardware implementations of such architectures and their potential for sensorimotor processing and robotics.Comment: Preprint of article submitted for publication in International Journal of Approximate Reasoning and accepted pending minor revision

    Directional and singular surface plasmon generation in chiral and achiral nanostructures demonstrated by Leakage Radiation Microscopy

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    In this paper, we describe the implementation of leakage radiation microscopy (LRM) to probe the chirality of plasmonic nanostructures. We demonstrate experimentally spin-driven directional coupling as well as vortex generation of surface plasmon polaritons (SPPs) by nanostructures built with T-shaped and Λ\Lambda- shaped apertures. Using this far-field method, quantitative inspections, including directivity and extinction ratio measurements, are achieved via polarization analysis in both image and Fourier planes. To support our experimental findings, we develop an analytical model based on a multidipolar representation of Λ\Lambda- and T-shaped aperture plasmonic coupler allowing a theoretical explanation of both directionality and singular SPP formation. Furthermore, the roles of symmetry breaking and phases are emphasized in this work. This quantitative characterization of spin-orbit interactions paves the way for developing new directional couplers for subwavelength routing

    Hand gesture recognition based on signals cross-correlation

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