179 resultados para visual object detection
Resumo:
Biological systems have facility to capture salient object(s) in a given scene, but it is still a difficult task to be accomplished by artificial vision systems. In this paper a visual selection mechanism based on the integrate and fire neural network is proposed. The model not only can discriminate objects in a given visual scene, but also can deliver focus of attention to the salient object. Moreover, it processes a combination of relevant features of an input scene, such as intensity, color, orientation, and the contrast of them. In comparison to other visual selection approaches, this model presents several interesting features. It is able to capture attention of objects in complex forms, including those linearly nonseparable. Moreover, computer simulations show that the model produces results similar to those observed in natural vision systems.
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Citrus canker is a serious disease caused by Xanthomonas citri subsp. citri bacteria, which infects citrus plants (Citrus spp.) leading to a large economic loss in citrus production worldwide. In Brazil citrus canker control is done by an official eradication campaign, therefore early detection of such disease is important to prevent greater economic losses. However, detection is difficult and so far it has been done by visual inspection of each tree. Suspicious leaves from citrus plants in the field are sent to the laboratory to confirm the infection by laboratory analysis, which is a time consuming. Our goal was to develop a new optical technique to detect and diagnose citrus canker in citrus plants with a portable field spectrometer unit. In this paper, we review two experiments on laser induced fluorescence spectroscopy (LIF) applied to detect citrus canker. We also present new data to show that the length of time a leaf has been detached is an important variable in our studies. Our results show that LIF has the potential to be applied to citrus plants.
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Although the oral cavity is easily accessible to inspection, patients with oral cancer most often present at a late stage, leading to high morbidity and mortality. Autofluorescence imaging has emerged as a promising technology to aid clinicians in screening for oral neoplasia and as an aid to resection, but current approaches rely on subjective interpretation. We present a new method to objectively delineate neoplastic oral mucosa using autofluorescence imaging. Autofluorescence images were obtained from 56 patients with oral lesions and 11 normal volunteers. From these images, 276 measurements from 159 unique regions of interest (ROI) sites corresponding to normal and confirmed neoplastic areas were identified. Data from ROIs in the first 46 subjects were used to develop a simple classification algorithm based on the ratio of red-to-green fluorescence; performance of this algorithm was then validated using data from the ROIs in the last 21 subjects. This algorithm was applied to patient images to create visual disease probability maps across the field of view. Histologic sections of resected tissue were used to validate the disease probability maps. The best discrimination between neoplastic and nonneoplastic areas was obtained at 405 nm excitation; normal tissue could be discriminated from dysplasia and invasive cancer with a 95.9% sensitivity and 96.2% specificity in the training set, and with a 100% sensitivity and 91.4% specificity in the validation set. Disease probability maps qualitatively agreed with both clinical impression and histology. Autofluorescence imaging coupled with objective image analysis provided a sensitive and noninvasive tool for the detection of oral neoplasia.
Resumo:
The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
Previous studies indicated that patients with atherosclerosis are predominantly infected by human cytomegalovirus (HCMV), but rarely infected by type 1 Epstein-Barr virus (EBV-1). In this study, atheromas of 30 patients who underwent aortocoronary bypass surgery with coronary endartherectomy were tested for the presence of these two viruses. HCMV occurred in 93.3% of the samples and EBV-1 was present in 50% of them. Concurrent presence of both pathogens was detected in 43.3% of the samples.
Resumo:
A redução da disponibilidade de espécies de madeiras nativas e seus efeitos na economia, associada ao fortalecimento dos conceitos de preservação ambiental, criou a necessidade de desenvolvimento de alternativas viáveis para utilização racional de espécies de reflorestamento. E uma das opções é a realização de classificação visual das peças. Autores de trabalhos desenvolvidos nessa linha de pesquisa verificaram a adequação das regras de classificação visual do Southern Pine Inspection Bureau (SPIB) dos EUA à madeira de Pinus do Brasil e apresentaram proposta para normalizar o processo de classificação visual dessa madeira. Nessa classificação, os aspectos com maior influência são: presença de nós, desvio de grã em relação ao eixo da peça e densidade de anéis de crescimento. Assim, esta pesquisa apresenta um estudo experimental que consistiu na classificação visual e determinação da resistência à tração de 85 peças de Pinus spp e um estudo teórico, que propôs uma equação para determinar a resistência à tração média de peças estruturais em função da classificação visual. Com este trabalho, foi possível observar a influência dos nós e dos anéis de crescimento sobre a resistência à tração das peças analisadas.
Resumo:
Onion (Allium cepa) is one of the most cultivated and consumed vegetables in Brazil and its importance is due to the large laborforce involved. One of the main pests that affect this crop is the Onion Thrips (Thrips tabaci), but the spatial distribution of this insect, although important, has not been considered in crop management recommendations, experimental planning or sampling procedures. Our purpose here is to consider statistical tools to detect and model spatial patterns of the occurrence of the onion thrips. In order to characterize the spatial distribution pattern of the Onion Thrips a survey was carried out to record the number of insects in each development phase on onion plant leaves, on different dates and sample locations, in four rural properties with neighboring farms under different infestation levels and planting methods. The Mantel randomization test proved to be a useful tool to test for spatial correlation which, when detected, was described by a mixed spatial Poisson model with a geostatistical random component and parameters allowing for a characterization of the spatial pattern, as well as the production of prediction maps of susceptibility to levels of infestation throughout the area.
Resumo:
A avaliação da dor em animais necessita da utilização de escalas de avaliação, que dependem da interpretação realizada por observadores. O objetivo do presente estudo foi avaliar a correlação entre a escala visual analógica (EVA), escala de Melbourne e os filamentos de Von Frey, na avaliação da dor pós-operatória em 42 cadelas adultas e saudáveis, submetidas à ovariossalpingohisterectomia (OSH). A dor pós-operatória foi avaliada por dois observadores cegos aos tratamentos analgésicos, em intervalos de uma hora, utilizando a EVA, a escala de Melbourne e os filamentos de Von Frey, aplicados ao redor da incisão cirúrgica. Foram considerados como critérios para realização da analgesia resgate uma pontuação de 50mm na EVA ou de 13 pontos na escala de Melbourne. A EVA revelou-se a escala mais sensível, uma vez que 100% dos animais receberam resgate seguindo esse método. Os valores obtidos na EVA e na escala de Melbourne determinaram boa correlação, com r=0,74, o que não ocorreu com os filamentos de Von Frey (r=-0,18). Já a correlação entre a escala de Melbourne e os filamentos de Von Frey foi de -0.37. Apesar de a EVA e a escala de Melbourne apresentarem boa correlação, sugere-se que se considere uma pontuação menor na escala de Melbourne como critério para administração de analgesia resgate.
Resumo:
To determine the presence of Brucella ovis in ovine from Paraíba State, in the Northeast region of Brazil, 80 animals slaughtered in the public slaughterhouse of Patos city were used. Before slaughter, blood samples were collected by jugular venopuncture from each animal, and after slaughter, testicles, epidydimus and uterus were aseptically collected. For the serological diagnosis of B. ovis and B. abortus infections, the agar gel immunodiffusion (AGID) and Rose Bengal (RBT) tests were carried out, respectively. In addition, microbiological culture and polymerase chain reaction (PCR) were performed on testicle, epidydimus and uterus samples. Six animals (7.5%) tested positive for the presence of B. ovis antibodies and all animals tested negative for the presence of B. abortus antibodies. One AGID-positive animal tested positive at uterine swab culture. PCR was able to amplify DNA of Brucella spp. from the pool of testicle, epidydimus and uterus samples from AGID-positive animals. This is the first report of isolation and detection of B. ovis DNA by PCR in ovine from the Northeast region of Brazil.
Resumo:
The objective of the present study was to improve the detection of B. abortus by PCR in organs of aborted fetuses from infected cows, an important mechanism to find infected herds on the eradication phase of the program. So, different DNA extraction protocols were compared, focusing the PCR detection of B. abortus in clinical samples collected from aborted fetuses or calves born from cows challenged with the 2308 B. abortus strain. Therefore, two gold standard groups were built based on classical bacteriology, formed from: 32 lungs (17 positives), 26 spleens (11 positives), 23 livers (8 positives) and 22 bronchial lymph nodes (7 positives). All samples were submitted to three DNA extraction protocols, followed by the same amplification process with the primers B4 and B5. From the accumulated results for organ, the proportion of positives for the lungs was higher than the livers (p=0.04) or bronchial lymph nodes (p=0.004) and equal to the spleens (p=0.18). From the accumulated results for DNA extraction protocol, the proportion of positives for the Boom protocol was bigger than the PK (p<0.0001) and GT (p=0.0004). There was no difference between the PK and GT protocols (p=0.5). Some positive samples from the classical bacteriology were negative to the PCR and viceversa. Therefore, the best strategy for B. abortus detection in the organs of aborted fetuses or calves born from infected cows is the use, in parallel, of isolation by classical bacteriology and the PCR, with the DNA extraction performed by the Boom protocol.
Resumo:
PURPOSE: To report a new, direct visual approach for rat pinealectomy. METHODS: Eighty adult female rats (Rattus norvegicus albinus EPM-1 strain) were weighted and anesthetized intraperitoneally with 15 mg/kg xylazine and 30 mg/kg ketamine. The animal was fastened to a dissection table, an incision was made in the skin and the subcutaneous tissue, bringing the lambda into view. The skullcap was opened with a dental drill, bringing the cerebral hemispheres and the superior sagittal sinus into view. The pineal gland, located under the venous sinus, was removed in a single piece using tweezers. Next, the bone fragment was returned to its place and the surgical layers were sutured. RESULTS: This new technique is easy to be done, avoids bleedings and removes only the pineal gland without damage to the remaining encephalon. In addition it makes possible the achievement of a sham surgery, allowing the pineal gland to remain intact. CONCLUSION: The proposed technique intends to facilitate studies aiming to better understanding the complexity and importance of the pineal gland on reproductive and other body systems.
Resumo:
Testing contexts have been shown to critically influence experimental results in psychophysical studies. One of these contexts that show important modulation of the behavioral effects of different stimulatory conditions is the separate (blocked) or mixed presentation of these stimulatory conditions. The study presents evidence that the apparent discriminabilities of two target stimuli can change according to which of these two testing contexts is used. A cross inside a ring and a vertical line inside a ring were presented as go stimuli in a go/no-go reaction time task. In one experiment, each of these stimuli was presented to a different group of volunteers and in another experiment they were presented to the same group of volunteers, randomly mixed in the blocks of trials. Similar reaction times were obtained for the two stimuli in the first experiment, and different reaction times (faster for the cross) in the second experiment. The latter result indicates that the two stimuli have different discriminabilities from the no-go stimulus; the cross having greater discriminability. This difference is however masked, presumably by the adoption of specific compensatory attentional sets, in a separate testing context.
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The naturally occurring clonal diversity among field isolates of the major human malaria parasite Plasmodium vivax remained unexplored until the early 1990s, when improved molecular methods allowed the use of blood samples obtained directly from patients, without prior in vitro culture, for genotyping purposes. Here we briefly review the molecular strategies currently used to detect genetically distinct clones in patient-derived P. vivax samples, present evidence that multiple-clone P. vivax infections are commonly detected in areas with different levels of malaria transmission and discuss possible evolutionary and epidemiological consequences of the competition between genetically distinct clones in natural human infections. We suggest that, when two or more genetically distinct clones are present in the same host, intra-host competition for limited resources may select for P. vivax traits that represent major public health challenges, such as increased virulence, increased transmissibility and antimalarial drug resistance.
Resumo:
Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.
Resumo:
O objetivo deste trabalho foi medir curvas de sensibilidade ao contraste de 10 crianças ouvintes e de 10 crianças com surdez pré-lingual, de 7 a 12 anos, utilizando frequências radiais circularmente concêntricas (FSCr) de 0,25-2,0 cpg em níveis baixos de luminância (0,7 cd/m²). Todos os participantes apresentavam acuidade visual normal e estavam livres de doenças oculares identificáveis. A FSCr foi medida com o método psicofísico da escolha forçada. Os resultados mostraram sensibilidade máxima na faixa de frequência radial de 0,25 cpg para os dois grupos. Os resultados mostraram ainda diferenças significantes entre as curvas de FSCr de crianças ouvintes e de crianças com surdez pré-lingual. Isto é, as crianças ouvintes precisaram de menos contraste do que as crianças surdas para detectar as frequências radiais. Esses resultados sugerem que, em níveis baixos de luminância, a FSCr das crianças ouvintes foi melhor do que a das crianças com surdez pré-lingual.