Search results for " Processing"
showing 10 items of 7549 documents
Evidentials and Epistemic Modality
2018
Abstract This chapter deals with the relation between the notional domains of information source and epistemic modality. It surveys various approaches to this relation and the cross-linguistic patterns of the way in which linguistic units (of diverse formats) with evidential or epistemic meanings develop extensions whereby they encroach into each other’s domains. Meaning extensions in either direction can adequately be captured, and confusion between both domains can be avoided, only if in the analysis of the meaning of such units (a) an onomasiological and semasiological perspective and (b) a coded-inferred divide are distinguished. Thus, epistemic extensions often arise as Generalized Con…
Applying logistic regression to relevance feedback in image retrieval systems
2007
This paper deals with the problem of image retrieval from large image databases. A particularly interesting problem is the retrieval of all images which are similar to one in the user's mind, taking into account his/her feedback which is expressed as positive or negative preferences for the images that the system progressively shows during the search. Here we present a novel algorithm for the incorporation of user preferences in an image retrieval system based exclusively on the visual content of the image, which is stored as a vector of low-level features. The algorithm considers the probability of an image belonging to the set of those sought by the user, and models the logit of this prob…
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…
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…
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 …
Modified LACIF filtering in background disjoint noise
2011
Abstract This work deals with pattern recognition methods based on correlations for images in the presence of noise. We propose a modification of the nonlinear Locally Adaptive Contrast Invariant Filter (LACIF) that yields correlation peaks that are invariant to linear intensity changes of the target but that has some limitations in the presence low variance nonoverlapping background noise. The modification of the filter implies a normalization by a global variance of several distributions. The estimation of the variance distributions is done locally by means of correlations. Experimental results as well as comparisons with the classical matched filter and the common LACIF are given.
Intensity invariant nonlinear correlation filtering in spatially disjoint noise.
2010
We analyze the performance of a nonlinear correlation called the Locally Adaptive Contrast Invariant Filter in the presence of spatially disjoint noise under the peak-to-sidelobe ratio (PSR) metric. We show that the PSR using the nonlinear correlation improves as the disjoint noise intensity increases, whereas, for common linear filtering, it goes to zero. Experimental results as well as comparisons with a classical matched filter are given.
View Planning Approach for Automatic 3D Digitization of Unknown Objects
2012
International audience; This paper addresses the view planning problem for the digitization of 3D objects without prior knowledge on their shape and presents a novel surface approach for the Next Best View (NBV) computation. The proposed method uses the concept of Mass Vector Chains (MVC) to define the global orientation of the scanned part. All of the viewpoints satisfying an orientation constraint are clustered using the Mean Shift technique to construct a first set of candidates for the NBV. Then, a weight is assigned to each mode according to the elementary orientations of its different descriptors. The NBV is chosen among the modes with the highest weights and which comply with the rob…
Combining similarity measures in content-based image retrieval
2008
The purpose of content based image retrieval (CBIR) systems is to allow users to retrieve pictures from large image repositories. In a CBIR system, an image is usually represented as a set of low level descriptors from which a series of underlying similarity or distance functions are used to conveniently drive the different types of queries. Recent work deals with combination of distances or scores from different and usually independent representations in an attempt to induce high level semantics from the low level descriptors of the images. Choosing the best method to combine these results requires a careful analysis and, in most cases, the use of ad-hoc strategies. Combination based on or…