4,416 research outputs found
Novo método iterativo de localização da câmera baseado no conceito de resection-intersection
A Odometria Visual Ă© o processo de estimar o movimento de um ente a partir de duas ou mais imagens fornecidas por uma ou mais câmeras. É uma tĂ©cnica de grande importância na visĂŁo computacional, com aplicações em diversas áreas tais como assistĂŞncia ao motorista e navegação de veĂculos autĂ´nomos, sistemas de realidade aumentada, veĂculos autĂ´nomos nĂŁo-tripulados (VANTs) e atĂ© mesmo na exploração interplanetária. Os mĂ©- todos mais comuns de Odometria Visual utilizam câmeras com visĂŁo estĂ©reo, atravĂ©s das quais Ă© possĂvel calcular diretamente as informações de profundidade de detalhes de uma cena, o que permite estimar as posições sucessivas das câmeras. A Odometria Visual Monocular estima o deslocamento de um objeto com base nas imagens fornecidas por uma Ăşnica câmera, o que oferece vantagens construtivas e operacionais embora exija processamento mais complexo. Os sistemas de Odometria Visual Monocular do tipo esparsos estimam a pose da câmera a partir de singularidades detectadas nas imagens, o que reduz significativamente o poder de processamento necessário, sendo assim ideal para aplica- ções de tempo real. Nessa Ăłptica, este trabalho apresenta um novo sistema de Odometria Visual Monocular esparsa para tempo real, validado em veĂculo instrumentado. O novo sistema Ă© baseado no conceito de Resection-Intersection, combinado com um novo teste de convergĂŞncia, e um mĂ©todo de refinamento iterativo para minimizar os erros de reproje- ção. O sistema foi projetado para ser capaz de utilizar diferentes algoritmos de otimização nĂŁo linear, tais como Gauss-Newton, Levenberg-Marquardt, Davidon-Fletcher-Powell ou Broyden–Fletcher–Goldfarb–Shannon. Utilizando o benchmark KITTI, o sistema proposto obteve um erro de translação em relação Ă distância mĂ©dia percorrida de 0, 86% e erro mĂ©dio de rotação em relação Ă distância mĂ©dia percorrida de 0.0024â—¦/m. O sistema foi desenvolvido em Python em uma Ăşnica thread, foi embarcado em uma placa Raspberry Pi 4B e obteve um tempo mĂ©dio de processamento de 775ms por imagem para os onze primeiros cenários do benchmark. O desempenho obtido neste trabalho supera os resultados de outros sistemas de Odometria Visual Monocular baseados no conceito de ResectionIntersection atĂ© o momento submetidos na classificação do benchmark KITTI.Visual Odometry is the process of estimating the movement of an entity from two or more images provided by one or more cameras. It is a technique ofmain concern in computer vision, with applications in several areas such as driver assistance and autonomous vehicle navigation, augmented reality systems, Unmanned Aerial Vehicle (UAV) and even in interplanetary exploration. Most common methods of Visual Odometry use stereo cameras, through which it is possible to directly calculate the depth information of details of a scene, which allows to estimate the successive positions of the cameras. Monocular Visual Odometry estimates the displacement of an object based on images provided by a single camera, which offers constructive and operational advantages although it requires more complex processing. Sparse-type Monocular Visual Odometry systems estimate the camera pose from singularities detected in the images, which significantly reduces the processing power required, thus making it ideal for real-time applications. In this perspective, this work presents a new Sparse Monocular visual Odometry system for real-time, validated on a instrumented vehicle. The new system is based on the Resection-Intersection concept, combined with an expanded convergence test, and an iterative refinement method to minimize reprojection errors. It was designed to be able to use different non-linear optimization algorithms, such as Gauss-Newton, Levenberg-Marquardt, Davidon-FletcherPowell or Broyden–Fletcher–Goldfarb–Shannon. Using the benchmark KITTI, the proposed system obtained a translation error in relation to the average distance traveled of 0.86% and an average rotation error in relation to the average distance covered of 0.0024â—¦/m. The system was developed in Python on a single thread, was embedded on a Raspberry Pi 4B board and an average processing time of 775ms per image for the first eleven scenarios of the benchmark. The results obtained in this work surpass the results obtained by other visual odometry systems based on the concept of Resection-Intersection so far submitted to the KITTI benchmark ranking
Automatic assessment of honey bee cells using deep learning
Temporal assessment of honey bee colony strength is required for different applications
in many research projects, which often involves counting the number of comb cells with
brood and food reserves multiple times a year. There are thousands of cells in each comb,
which makes manual counting a time-consuming, tedious and thereby an error-prone
task. Therefore, the automation of this task using modern imaging processing techniques
represents a major advance. Herein, we developed a software capable of (i) detecting
each cell from comb images, (ii) classifying its content and (iii) display the results to
the researcher in a simple way. The cells’ contents typically display a high variation of
patterns which make their classification by software a challenging endeavour. To address
this challenge, we used Deep Neural Networks (DNNs). DNNs are known for achieving the
state of art in many fields of study including image classification, because they can learn
features that best describe the content being classified by themselves. Our DNN model
was trained with over 70,000 manually labelled cell images whose cells were separated
into seven classes. Our contribution is an end-to-end software capable of doing automatic
background removal, cell detection, and classification of cell content based on an input
comb image. With this software, colony assessment achieves an average accuracy of 94%
across the seven classes in our dataset, representing a substantial progress regarding the
approximation methods (e.g. Lieberfeld) currently used by honey bee researchers and
previous techniques based on machine learning that used handmade features like colour
and texture.A análise temporal sobre a qualidade e força de colĂ´nias de abelha melĂfera (Apis mellifera
L.) é necessária em muitos projetos de pesquisa. Ela pode ser realizada contando alvéolos
com alimento (pólen e néctar) e criação. É comum que ela seja feita diversas vezes ao
ano. A grande quantidade de alvéolos em cada favo torna a tarefa demorada e tediosa
ao pesquisador. Assim, frequentemente essa contagem Ă© feita forma aproximada usando
métodos como o de Lieberfeld. Automatizar este processo usando técnicas modernas de
processamento de imagem representa um grande avanço, pois resultados mais precisos e
padronizados poderĂŁo ser obtidos em menos tempo. O objetivo deste trabalho Ă© construir
de um software capaz de detectar, classificar e contar alvéolos a partir de uma imagem.
Após, ele deverá apresentar os dados de forma simplificada ao usuário. Para tratar da alta
variação de padrões como textura, cor e iluminação presente nas alvéolos, usaremos Deep
Neural Network (DNN), que são modelos computacionais conhecidos por terem alcançado
o estado da arte em várias tarefas relacionadas a processamento de sinais e imagens. Para o
treinamento desses modelos utilizamos mais de 70.000 alvéolos anotadas por um apicultor
experiente, separadas em sete classes. Entre nossas contribuições estão métodos de préprocessamento
que garantem uma alta taxa de detecção de alvéolos, aliados a modelos
de segmentação baseados em DNNs que asseguram uma baixa taxa de falsos positivos.
Com nossos classificadores conseguimos uma acurácia média de 94% em nosso dataset e
obtivemos resultados superiores a outros métodos baseados em contagens aproximadas e
técnicas de análise por imagem que não utilizam DNNs.This research was conducted in the framework of the project BEEHOPE, funded
through the 2013-2014 BiodivERsA/FACCE-JPI Joint call for research proposals, with
the national founders FCT(Portugal), CNRS(France), and MEC(Spain)
Thermal conductivity of calcium silicate boards at high temperatures: an experimental approach
Thermal conductivity analysis of fire insulation materials is of great importance for determining the critical temperature of structures. The magnitude of this thermal property has a significant influence on the analysis of temperature distribution and heat flow which depends essentially on the thermal properties of the protection material. Knowing accurate information about the effects of high temperatures on thermal conductivity is an important prerequisite for a performance based design of fire safety in buildings. Therefore, an investigation of two different calcium silicate boards has been performed to demonstrate how the thermal conductivity is affected when exposed to high temperatures. A set of experimental tests is presented. They were conducted in different techniques such as: the transient plane source (TPS) and the guarded hot plate (GHP).info:eu-repo/semantics/publishedVersio
Conjugate Cooling of a Discrete Heater in Laminar Channel Flow
Electronic components are usually assembled on printed circuit boards cooled by forced airflow. When the spacing between the boards is small, there is no room to employ a heat sink on critical components. Under these conditions, the components? thermal control may depend on the conductive path from the heater to the board in addition to the direct convective heat transfer to the airflow.The conjugate forced convection-conduction heat transfer from a two-dimensional strip heater flush mounted to a finite thickness wall of a parallel plates channel cooled by a laminar airflow was investigated numerically. A uniform heat flux was generated along the strip heater surface. Under steady state conditions, a fraction of the heat generation was transferred by direct convection to the airflow in the channel and the remaining fraction was transferred by conduction to the channel wall. The lower surface of the channel wall was adiabatic, so that the heat conducted from the heater to the plate eventually returned to the airflow. A portion of it returned upstream of the heater, preheating the airflow before it reached the heater surface. Due to this, it was convenient to treat the direct convection from the heater surface to the airflow by the adiabatic heat transfer coefficient. The flow was developed from the channel entrance, with constant properties.The conjugate problem was solved numerically within a single solution domain comprising both the airflow region and the solid wall of the channel. The results were obtained for the channel flow Reynolds number ranging from about 600 to 1900, corresponding to average airflow velocities from 0.5 m/s to 1.5 m/s. The effects of the solid wall to air thermal conductivities ratio were investigated in the range from 10 to 80, typical of circuit board materials. The wall thickness influence was verified from 1 mm to 5 mm. The results indicated that within these ranges, the conductive substrate wall provided a substantial enhancement of the heat transfer from the heater, accomplished by an increase of its average adiabatic surface temperature.278286Conselho Nacional de Desenvolvimento CientĂfico e TecnolĂłgico (CNPq
Improving Random Access with NOMA in mMTC XL-MIMO
The extra-large multiple-input multiple-output (XL-MIMO) architecture has
been recognized as a technology for supporting the massive MTC (mMTC),
providing very high-data rates in high-user density scenarios. However, the
large dimension of the array increases the Rayleigh distance (dRayl), in
addition to obstacles and scatters causing spatial non-stationarities and
distinct visibility regions (VRs) across the XL array extension. We investigate
the random access (RA) problem in crowded XL-MIMO scenarios; the proposed
grant-based random access (GB-RA) protocol combining the advantage of
non-orthogonal multiple access (NOMA) and strongest user collision resolutions
in extra-large arrays (SUCRe-XL) named NOMA-XL can allow access of two or three
colliding users in the same XL sub-array (SA) selecting the same pilot
sequence. The received signal processing in a SA basis changes the dRayl,
enabling the far-field planar wavefront propagation condition, while improving
the system performance. The proposed NOMA-XL GB-RA protocol can reduce the
number of attempts to access the mMTC network while improving the average sum
rate, as the number of SA increases.Comment: 13 pages, 5 figures, 1 table, conference VTC 2023. arXiv admin note:
substantial text overlap with arXiv:2303.0053
Para uma nova caixa de Pandora: esboço de um roteiro heurĂstico pela sociologia da mĂşsica
Ainda que a mĂşsica esteja presente nas obras de autores pioneiros da sociologia (Max Weber e Georg Simmel), nĂŁo Ă© possĂvel falar em um campo devidamente consistente do fenĂ´meno musical dentro dos estudos sociolĂłgicos, nĂŁo obstante os trabalhos de alguns pesquisadores (Simon Frith, Andy Bennett, Antoine Hennion, Tia De Nora, dentre outros), impulsionados em grande parte pelo cultural turn ocorrida na sociologia em meados dos anos de 1970. Tendo em vista este panorama, o presente artigo tem como objetivo contribuir com as discussões sobre o estado da arte da sociologia da mĂşsica a partir das seguintes questões: a) o equilĂbrio necessário entre a abordagem estĂ©tica da mĂşsica e a sua devida contextualização social; b) o papel importante da mĂşsica popular em especial do pop-rock na conformação das identidades/práticas de segmentos geracionais, simbĂłlicos e culturais especĂficos; c) o incremento com ĂŞnfase especial para o caso portuguĂŞs de uma sociologia cultural que tem a mĂşsica enquanto tema-chave de suas preocupações; d) as contribuições especĂficas da sociologia para a análise dos gĂŞneros musicais com ĂŞnfase especial para o caso do rock alternativo.Although music is present in the works of pioneering authors of sociology (Max Weber and Georg Simmel), it is not possible to speak about a properly consistent field of music within sociological studies, despite the work of some researchers (Simon Frith, Andy Bennett, Antoine Hennion, Tia De Nora, among others), driven in large part by the cultural turn taking place in sociology in the mid-1970s. In view of this panorama, this article aims to contribute to the discussions on the state of the art of the sociology of music from the following questions: a) the necessary balance between the aesthetic approach of music and its due social contextualization; b) the important role of popular music - especially pop-rock - in shaping the identities / practices of specific generational, symbolic and cultural segments; c) the increase - with special emphasis on the Portuguese case - of a cultural sociology that has music as a key theme of its concerns; d) the specific contributions of sociology to the analysis of musical genres - with special emphasis on the case of alternative rock
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