1,721,168 research outputs found
Domain invariant hierarchical embedding for grocery products recognition
No full textRecognizing packaged grocery products based solely on appearance is still an open issue for modern computer vision systems due to peculiar challenges. Firstly, the number of different items to be recognized is huge (i.e., in the order of thousands) and rapidly changing over time. Moreover, there exist a significant domain shift between the images that should be recognized at test time, taken in stores by cheap cameras, and those available for training, usually just one or a few studio-quality images per product. We propose an end-to-end architecture comprising a GAN to address the domain shift at training time and a deep CNN trained on the samples generated by the GAN to learn an embedding of product images that enforces a hierarchy between product categories. At test time, we perform recognition by means of K-NN search against a database consisting of just one reference image per product. Experiments addressing recognition of products present in the training datasets as well as different ones unseen at training time show that our approach compares favorably to state-of-the-art methods on the grocery recognition task and generalize fairly well to similar ones
Fast template matching using bounded partial correlation
No full textThis paper describes a novel, fast template-matching technique, referred to as bounded partial correlation (BPC), based on the normalised cross-correlation (NCC) function. The technique consists in checking at each search position a suitable elimination condition relying on the evaluation of an upper-bound for the NCC function. The check allows for rapidly skipping the positions that cannot provide a better degree of match with respect to the current best-matching one. The upper-bounding function incorporates partial information from the actual cross-correlation function and can be calculated very efficiently using a recursive scheme. We show also a simple improvement to the basic BPC formulation that provides additional computational benefits and renders the technique more robust with respect to the parameters choice
A sufficient condition based on the Cauchy-Schwarz inequality for efficient template matching
No full textThe paper proposes a technique aimed at reducing the number of calculations required to carry out an exhaustive template matching process based on the Normalized Cross Correlation (NCC). The technique deploys an effective sufficient condition, relying on the recently introduced concept of bounded partial correlation, that allows rapid elimination of the points that can not provide a better cross-correlation score with respect to the current best candidate. In this paper we devise a novel sufficient condition based on the Cauchy-Schwarz inequality and compare the experimental results with those attained using the standard NCC-based template matching algorithm and the already known sufficient condition based on the Jensen inequality
Transvaginal administration of estriol in postmenopausal urogynecological disorders
No full textThe Authors carried out an open, non-controlled clinical trial in order to evaluate the clinical efficacy of estriol administered by the vaginal route (0.0125% cream) in cystourethropathic diseases caused by estrogenic insufficiency. All the 45 patients recruited (mean age 51.6 years) had been in menopause from 6 to 24 months; all of them have been treated with 0.5 mg estriol daily for 2 weeks; furthermore the treatment has been continued with the same dose of the hormone for the following 4 weeks but using an alternating daily administration. Among the parameters taken into consideration for the evaluation of the patients, a urodynamic examination has been also included. The final results have been considered very satisfactory showing a very significant improvement concerning every urodynamic test. Similar results have been obtained considering the symptomatologic point of view. On the basis of these results, the Authors concluded that estriol vaginal cream formulation represents a valuable therapeutical possibility in the treatment of patients affected by urogynecological diseases caused by estrogenic insufficiency in post-menopausal conditions
SAFFIRE: System for Autonomous Feature Filtering and Intelligent ROI Estimation
No full textThis work introduces a new framework, named SAFFIRE, to automatically extract a dominant recurrent image pattern from a set of image samples. Such a pattern shall be used to eliminate pose variations between samples, which is a common requirement in many computer vision and machine learning tasks. The framework is specialized here in the context of a machine vision system for automated product inspection. Here, it is customary to ask the user for the identification of an anchor pattern, to be used by the automated system to normalize data before further processing. Yet, this is a very sensitive operation which is intrinsically subjective and requires high expertise. Hereto, SAFFIRE provides a unique and disruptive framework for unsupervised identification of an optimal anchor pattern in a way which is fully transparent to the user. SAFFIRE is thoroughly validated on several realistic case studies for a machine vision inspection pipeline
Coarse-to-fine strategy for robust and efficient change detectors
No full textWe present a novel approach to change detection based on a coarse-to-fine strategy. An efficient coarse-level detection is proposed that filters out most of the possible false changes, thus attaining reliable and tight course-grain super-masks of the truly changed areas. The subsequent fine-level detection can thus "focus the attention" just on the "interesting" parts of the frame and perform a robust selective background updating procedure by considering the complement of these masks. Besides, the analysis of a strip of pixels surrounding each coarse-grain blob allows to infer information on light changes possibly occurring in the blob's vicinity. Although any algorithm can be used as the final fine-level detection, here we show how the approach applies to a particular algorithm we devised, based on a non-parametric statistical modelling of the camera noise
Detection of circular objects by wave propagation on a mesh-connected computer
No full textCircular objects can be detected in low-contrast and/or blurred images by propagating intensity values according to a two-dimensional wave equation and then finding peaks generated by constructive interference. The paper proposes a parallel algorithm for SIMD mesh-connected computers (MCCs) that is based on this approach; the algorithm presents a fast difference scheme and a search for peaks based on spatio-temporal extremes, and also incorporates absorbing boundary conditions. We describe the parallel algorithm using machine-independent pseudo-code since our goal is to provide detailed guidelines for implementation on MCCs. Pseudo-code statements are expanded with respect to a basic model′s instruction set in order to evaluate costs associated with the algorithm′s subtasks and discuss implementation choices. © 1995 Academic Press, Inc
An efficient algorithm for exhaustive template matching based on normalized cross correlation
No full textThis work proposes a novel technique aimed at improving the performance of exhaustive template matching based on the normalized cross correlation (NCC). An effective sufficient condition, capable of rapidly pruning those match candidates that could not provide a better cross correlation score with respect to the current best candidate, can be obtained exploiting an upper bound of the NCC function. This upper bound relies on partial evaluation of the crosscorrelation and can be computed efficiently, yielding a significant reduction of operations compared to the NCC function and allows for reducing the overall number of operations required to carry out exhaustive searches. However, the bounded partial correlation (BPC) algorithm turns out to be significantly data dependent. In this paper we propose a novel algorithm that improves the overall performance of BPC thanks to the deployment of a more selective sufficient condition which allows for rendering the algorithm significantly less data dependent. Experimental results with real images and actual CPU time are reported. © 2003 IEEE
Real-time dense stereo on a personal computer
No full textThis paper presents a stereo algorithm that enables real time dense disparity measurements on standard personal computers. Unlike many other dense stereo algorithms, which are based on two matching phases, the proposed algorithm relies on a single matching phase and allows for rejecting unreliable matches by exploiting violations of the uniqueness constraint and analysing the behaviour of the correlation scores. The overall algorithm has been carefully optimised using very efficient calculation schemes and deploying massively the SIMD parallel processing capabilities available nowadays in state-of-the-art general purpose microprocessors. The paper describes the algorithm and the optimisation strategies, and provides experimental results obtained on stereo pairs with ground-truth as well as execution times measurements
The TRbeta-selective agonist, GC-1, stimulates mitochondrial oxidative processes to a lesser extent than triiodothyronine
No full textJ Endocrinol. 2010 Jun;205(3):279-89. Epub 2010 Apr 1.
The TRbeta-selective agonist, GC-1, stimulates mitochondrial oxidative processes to a lesser extent than triiodothyronine.
Venditti P, Chiellini G, Di Stefano L, Napolitano G, Zucchi R, Columbano A, Scanlan TS, Di Meo S.
SourceDipartimento delle Scienze Biologiche, Sezione di Fisiologia, Università di Napoli Federico II, Via Mezzocannone 8, I-80134 Napoli, Italy. [email protected]
Abstract
Specific tissue responses to thyroid hormone are mediated by the hormone binding to two subtypes of nuclear receptors, TRalpha and TRbeta. We investigated the relationship between TRbeta activation and liver oxidative metabolism in hypothyroid rats treated with equimolar doses of triiodothyronine (T(3)) and GC-1, a TRbeta agonist. T(3) treatment produces increases in O(2) consumption and H(2)O(2) production higher than those elicited by GC-1. The greater effects of T(3) on oxidative processes are linked to the higher hormonal stimulation of the content of respiratory chain components including autoxidizable electron carriers as demonstrated by the measurement of activities of respiratory complexes and H(2)O(2) generation in the presence of respiratory inhibitors. It is conceivable that these differential effects are dependent on the inability of GC-1 to stimulate TRalpha receptors that are likely involved in the expression of some components of the respiratory chain. The greater increases in reactive oxygen species production and susceptibility to oxidants exhibited by mitochondria from T(3)-treated rats are consistent with their higher lipid and protein oxidative damage and lower resistance to Ca(2)(+) load. The T(3) and GC-1 effects on the expression levels of nuclear respiratory factor-1 and -2 and peroxisome proliferator-activated receptor-gamma coactivator-1alpha suggest the involvement of respiratory factors in the agonist-linked changes in mitochondrial respiratory capacities and H(2)O(2) production.
PMID:20360308[PubMed - indexed for MEDLINE
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