Search results for "artificial intelligence"
showing 10 items of 6122 documents
A Conversational Agent Based on a Conceptual Interpretation of a Data Driven Semantic Space
2005
In this work we propose an interpretation of the LSA framework which leads to a data-driven “conceptual” space creation suitable for an “intuitive” conversational agent. The proposed approach allows overcoming the limitations of traditional, rule-based, chat-bots, leading to a more natural dialogue.
A word prediction methodology for automatic sentence completion
2015
Word prediction generally relies on n-grams occurrence statistics, which may have huge data storage requirements and does not take into account the general meaning of the text. We propose an alternative methodology, based on Latent Semantic Analysis, to address these issues. An asymmetric Word-Word frequency matrix is employed to achieve higher scalability with large training datasets than the classic Word-Document approach. We propose a function for scoring candidate terms for the missing word in a sentence. We show how this function approximates the probability of occurrence of a given candidate word. Experimental results show that the proposed approach outperforms non neural network lang…
Spatio-Temporal Saliency Detection in Dynamic Scenes using Local Binary Patterns
2014
International audience; Visual saliency detection is an important step in many computer vision applications, since it reduces further processing steps to regions of interest. Saliency detection in still images is a well-studied topic. However, videos scenes contain more information than static images, and this additional temporal information is an important aspect of human perception. Therefore, it is necessary to include motion information in order to obtain spatio-temporal saliency map for a dynamic scene. In this paper, we introduce a new spatio-temporal saliency detection method for dynamic scenes based on dynamic textures computed with local binary patterns. In particular, we extract l…
A family of kernel anomaly change detectors
2014
This paper introduces the nonlinear extension of the anomaly change detection algorithms in [1] based on the theory of reproducing kernels. The presented methods generalize their linear counterparts, under both the Gaussian and elliptically-contoured assumptions, and produce both improved detection accuracies and reduced false alarm rates. We study the Gaussianity of the data in Hilbert spaces with kernel dependence estimates, provide low-rank kernel versions to cope with the high computational cost of the methods, and give prescriptions about the selection of the kernel functions and their parameters. We illustrate the performance of the introduced kernel methods in both pervasive and anom…
Content based segmentation of patterned wafers
2004
We extend our previous work on the image segmentation of electronic structures on patterned wafers to improve the defect detection process on optical inspection tools. Die-to-die wafer in- spection is based on the comparison of the same area on two neigh- boring dies. The dissimilarities between the images are a result of defects in this area of one of the dies. The noise level can vary from one structure to the other, within the same image. Therefore, seg- mentation is required to create a mask and apply an optimal thresh- old in each region. Contrast variation on the texture can affect the response of the parameters used for the segmentation. We show a method to anticipate these variation…
Integration of multiple range and intensity image pairs using a volumetric method to create textured three-dimensional models
2001
We present a volumetric approach to three-dimensional (3D) object modeling that differs from previous techniques in that both object texture and geometry are considered in the reconstruc- tion process. The motivation for the research is the simulation of a thermal tire inspection station. Integrating 3D geometry information with two-dimensional thermal images permits the thermal informa- tion to be displayed as a texture map on the tire structure, enhanc- ing analysis capabilities. Additionally, constructing the tire geometry during the inspection process allows the tire to be examined for structural defects that might be missed if the thermal data were textured onto a predefined model. Exp…
Pattern image enhancement by extended depth of field
2014
Abstract Most optical defect localization techniques such as dynamic laser stimulation or photon emission microscopy require a pattern image of the device to be taken. The main purpose is for device navigation, but it also enables the analyst to identify the location of the monitored activity by superimposing it onto the pattern image. The defect localization workflow usually starts at low or medium magnification. At these scales, several factors can lead to a lack of orthogonality of the sample with the optical axis of the system. Therefore, images can be locally out of focus and poorly resolved. In this paper, a method based on Depth of Field Extension is suggested to correct the pattern …
Validation of a Reinforcement Learning Policy for Dosage Optimization of Erythropoietin
2007
This paper deals with the validation of a Reinforcement Learning (RL) policy for dosage optimization of Erythropoietin (EPO). This policy was obtained using data from patients in a haemodialysis program during the year 2005. The goal of this policy was to maintain patients' Haemoglobin (Hb) level between 11.5 g/dl and 12.5 g/dl. An individual management was needed, as each patient usually presents a different response to the treatment. RL provides an attractive and satisfactory solution, showing that a policy based on RL would be much more successful in achieving the goal of maintaining patients within the desired target of Hb than the policy followed by the hospital so far. In this work, t…
Real And Positive Filter Based On Circular Harmonic Expansion
1989
A real and positive filter for pattern recognition is presented. The filter, based on the circular harmonic (CH) expansion of a real function, is partially rotation invariant. As it is real and positive, the filter can be recorded on a transparency as an amplitude filter. Computer simulations of character recognition show a partial rotation invariance of about 40°. Optical experiments agree with these results and with acceptable discrimination between different characters. Nevertheless, due to experimental difficulties, the method is onerous for use in general pattern recognition problems.
Perceptually weighted optical flow for motion-based segmentation in MPEG-4 paradigm
2000
In the MPEG-4 paradigm, the sequence must be described in terms of meaningful objects. This meaningful, high-level representation should emerge from low-level primitives such as optical flow and prediction error which are the basic elements of previous-generation video coders. The accuracy of the high-level models strongly depends on the robustness of the primitives used. It is shown how perceptual weighting in optical flow computation gives rise to better motion estimates which consistently improve motion-based segmentation compared to equivalent unweighted motion estimates.