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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Daniel Zanotta Vinicius Sales Ademir Marques Andre Luiz Durante Spigolon Luiz Gonzaga Maurício Roberto Veronez Vizlab — X-Reality and GeoInformatics Lab UNISINOS - São Leopoldo RS Brazil Graduate Program in Applied Computing at Vale do Rio dos Sinos University São Leopoldo RS Brazil PETROBRAS - Petrobras Research and Development Center (CENPES) RJ Brazil

Improvement in spatial resolution of remote sensing images will always be a hot-topic since the sharpening of image objects is mandatory for many appications. Even thought image instruments have received great improvements in the recent years, super-resolution techniques are welcome to increase even more the level of quality of the data for further interpretations. In this paper we present a multi-frame super-resolution approach that uses a set of UAV images acquired at the same spot, but with slight different perspectives caused by random fluctuations. The small off-sets between consecutive pixels of the low spatial resolution images are considered at subpixel level to feed an arithmetic system of equations able to produce high resolution pixels, which are the unknowns of the system. The results are soundness and could show visual enhancement. However, further developments is need to in deep undertanding and possible advancement of the designed approach.

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Mineralogical Classification of Sedimentary Rocks by Spectral Matching Techniques Based on Library and Field-Work References

Mineralogical Classification of Sedimentary Rocks by Spectra...

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Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS

作者： Daniel C. Zanotta Lais V. De Souza Marcelo K. De Souza Alysson S. Ayres Vinícius F. Sales Graciela R. Racolte Delano M. Ibanez Luiz G. Silveira Maurício R. Veronez Vizlab — X-Reality and GeoInformatics Lab UNISINOS São Leopoldo RS Brazil Graduate Program in Applied Computing at Vale do Rio dos Sinos University São Leopoldo RS Brazil PETROBRAS - Petrobras Research and Development Center (CENPES) RJ Brazil

ISBN: (数字)9798331513139

ISBN: (纸本)9798331513146

Sedimentary rocks are of great importance for the oil and gas industry. Spectral matching using known references made on hyperspectral images is one of the most rapid and cost effective alternatives for the detailed analysis in these areas, since they can adequately catch the specific absorption features of the multiple minerals available. In many initiatives, scientists run the methods with standard spectral references, usually from spectral libraries or samples from other places. However, for the success of their application, they must be used along with spectral references that accurately describe the actual constituents of the surface. In this paper we scrutinize three different ways for mineralogical mapping performed by spectral matching techniques. The results showed that using reference spectra from samples collected directly on the surveyed environment can considerably improve the results, reaching high scores, pointing out that many places share common substances, but each specific material has particular differences that cannot be generalized.

关键词： Costs Systematics Signal processing Rocks Gas industry Libraries Minerals Petroleum industry Standards Hyperspectral imaging

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Indirect Calibration of Hyperspectral Images Using Rock Samples

Indirect Calibration of Hyperspectral Images Using Rock Samp...

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Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS

作者： Daniel C. Zanotta Leonardo D. Araújo Marcelo K. De Souza Delano M. Ibanez Luiz G. Silveira Maurício R. Veronez Vizlab — X-Reality and GeoInformatics Lab UNISINOS São Leopoldo RS Brazil Graduate Program in Applied Computing at Vale do Rio dos Sinos University São Leopoldo RS Brazil PETROBRAS - Petrobras Research and Development Center (CENPES) RJ Brazil

ISBN: (数字)9798331513139

ISBN: (纸本)9798331513146

This paper presents a methodology for the indirect calibration of hyperspectral images using radiometric measurements from field samples. While hyperspectral imaging (HSI) is essential in remote sensing, its accuracy depends on precise calibration, which is often challenging in the field. Most approaches rely on a single standard panel used as absolute reference and the empirical line method. This often leads to mistakes and uncertainties in the analysis. In this paper we propose an alternative that utilizes radiometric data from rock samples with known spectral properties to indirectly calibrate hyperspectral images. The results show specific improvements in accuracy, particularly in the shape of the curves, compared to standard calibration method. The calibrated images offer better material differentiation and more reliable spectral signatures, which are crucial for geological mapping and mineral exploration. This approach can enhance the reliability of hyperspectral data analysis in geological and environmental studies, especially in situations where time and logistics are challenging.

关键词： Accuracy Uncertainty Coal Signal processing Rocks Radiometry Calibration Minerals Standards Hyperspectral imaging

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2D Basement Relief Inversion using Sparse Regularization.

arXiv

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arXiv 2024年

作者： Barboza, Francisco Márcio da Cunha Romão Silva, E. Arthur Anthony de Carvalho, Bruno Motta Department of Computing and Technology Federal University of Rio Grande do Norte Rio Grande do Norte Caicó Brazil Graduate Program on Systems and Computing Federal University of Rio Grande do Norte Rio Grande do Norte Natal Brazil Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Rio Grande do Norte Natal Brazil

Basement relief gravimetry is a key application in geophysics, particularly important for oil exploration and mineral prospecting. It involves solving an inverse geophysical problem, where the parameters of a geological model are inferred from observed data. In this context, the geological model consists of the depths of constant-density prisms representing the basement relief, and the data correspond to the gravitational anomalies caused by these prisms. Inverse geophysical problems are typically ill-posed, as defined by Hadamard, meaning that small perturbations in the data can result in large variations in the solutions. To address this instability, regularization techniques, such as those proposed by Tikhonov, are employed to stabilize the solutions. This study presents a comparative analysis of various regularization techniques applied to the gravimetric inversion problem, including Smoothness Constraints, Total Variation, the Discrete Cosine Transform (DCT), and the Discrete Wavelet Transform (DWT) using Daubechies D4 wavelets. Optimization methods are commonly used in inverse geophysical problems because of their ability to find optimal parameters that minimize the objective function—in this case, the depths of the prisms that best explain the observed gravitational anomalies. The Genetic Algorithm (GA) was selected as the optimization technique. GA is based on Darwinian evolutionary theory, specifically the principle of natural selection, where the fittest individuals in a population are selected to pass on their traits. In optimization, this translates to selecting solutions that most effectively minimize the objective function. The results, evaluated using fit metrics and cumulative error analysis, demonstrate the effectiveness of all the regularization techniques and the Genetic Algorithm. Among the methods tested, the Smoothness constraint was briefly the most effective for the first and second synthetic models. For the third model, which was based on re

关键词： Discrete wavelet transforms

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On Self-Organizing Feature Map (SOFM) Formation by Direct Optimization Through a Genetic Algorithm

On Self-Organizing Feature Map (SOFM) Formation by Direct Op...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： José Everardo B. Maia Guilherme A. Barreto André L.V. Coelho Department of Teleinformatics Engineering Federal University of Ceará Fortaleza Ceara Brazil Department of Statistics and Computing State Univ. of Ceara Fortaleza Ceara Brazil Department of Statistics and Computing State University of Ceará Fortaleza Ceara Brazil Department of Teleinformatics Engineering Federal Univ. of Ceara Fortaleza Ceara Brazil Graduate Program in Applied Informatics University of Fortaleza Fortaleza Ceara Brazil

This paper examines the formation of self-organizing feature maps (SOFM) by the direct optimization of a cost function through a genetic algorithm (GA). The resulting SOFM is expected to produce simultaneously a topologically correct mapping between input and output spaces and a low quantization error. The proposed approach adopts a cost (fitness) function which is a weighted combination of indices that measure these two aspects of the map quality, specifically, the quantization error and the Pearson correlation coefficient between the corresponding distances in input and output spaces. The resulting maps are compared with those generated by the Kohonen's self-organizing map (SOM) algorithm in terms of the quantization error (QE), the weighted topological error (WTE) and the Pearson correlation coefficient (PCC) indices. The experiments show the proposed approach produces better values of the quality indices as well as is more robust to outliers.

关键词： Gallium Neurons Arrays Genetic algorithms Indexes Optimization Genetics

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Analysis of Positional and Geometric Accuracy of Objects in Survey with Unmanned Aerial Vehicle (UAV)

Analysis of Positional and Geometric Accuracy of Objects in ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gabriel Soares Leonardo Campos Inocencio Maurício Roberto Veronez Luiz Gonzaga da Silveira Fabiane Bordin Fernando Pinho Marson UNISINOS Advanced Visualization & Geoinformatics Laboratory São Leopoldo RS Brazil Graduate Program on Applied Computing - UNISINOS São Leopoldo RS Brazil São Leopoldo RS Brazil Universidade do Vale do Rio dos Sinos Sao Leopoldo RS BR

This study aimed the analysis of the positional and geometric accuracy of objects in orthomosaics obtained through different unmanned aerial vehicle (UAV) data processing software covering an area located within Universidade do Vale do Rio dos Sinos - UNISINOS in São Leopoldo, RS. A total of nine ground control points (GCP) and twenty checkpoints were surveyed in order register and classify the processed orthomosaics according to the cartographic accuracy standard - Padrão de Exatidão Cartográfica (PEC). Four software was employed to process the UAV data: Pix4D mapper, Agisoft PhotoScan, Menci APS and Bentley Context Capture. The results obtained from each software were compared and identified the smallest distortions when processing with and without ground control points. The flight was executed at a height of 90m with 60% sidelap and 80% overlap using an ST800 UAV equipped with a Sony NEX-7 small format non-metric camera with 24 megapixels resolution. The software GeoPEC was used to classify the orthomosaics according to PEC. For data processed with ground control points all orthomosaics were classified “Class A” in 1/500 scale, however, only Menci APS did not present a trend line via t-student test. On the other hand, Menci APS presented the worst results without the ground control points. In processing with GCP, all orthomosaics obtained optimum results with an approximated error of 2,5 m 2 , about 0.03% of the area.

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Tunable Source of Quantum-Correlated Photons with Integrated Pump Rejection in a Silicon CMOS Platform

Tunable Source of Quantum-Correlated Photons with Integrated...

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Frontiers in Optics + Laser Science 2021, FiO+LS 2021 - Part of Frontiers in Optics, FiO 2021

作者： Fargas Cabanillas, Josep M. Kramnik, Danielius Ramesh, Anirudh Gentry, Cale M. Stojanović, Vladimir Kumar, Prem Popović, Miloš A. Department of Electrical and Computer Engineering Photonics Center Boston University BostonMA02215 United States Department of Electrical Engineering and Computer Science UC Berkeley BerkeleyCA94720 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

ISBN: (纸本)9781557528209

A wavelength-tunable, silicon photon-pair source based on spontaneous four-wave mixing, integrated with a pump rejection filter in a single, flip-chip packaged CMOS chip, is demonstrated with a coincidence-to-accidentals ratio of 9.1 with no off-chip pump filtering. Frontiers in Optics / Laser Science © Optica Publishing Group 2021.

关键词： CMOS integrated circuits

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Immersive Paleontological Experience Through Virtual and Augmented Reality Representation

Immersive Paleontological Experience Through Virtual and Aug...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gustavo C. Almeida Daniel C. Zanotta Taina T. Guimaraes Ademir Marques Rodrigo S. Horodyski Luiz Gonzaga Maurício R. Veronez Vinícius C. Souza Vizlab — X-Reality and GeoInformatics Lab UNISINOS São Leopoldo RS Brazil Graduate Program in Applied Computing at Vale do Rio dos Sinos University São Leopoldo RS Brazil Rio Grande do Sul Geological History Museum UNISINOS São Leopoldo RS Brazil

Virtual reality systems have been extending their usability in many areas that could not be contemplated before. One of these fields is paleontology, which can now use virtual reality to build realistic models of real fossils with many goals, including preservation of originals, optimized visualization, or even for restoring missing parts. In this paper we present an immersive system where a entire scenario is reconstructed using digital photogrammetry and Mosis LAB application. The system has shown useful for many applications from touristic purposes and paleontological studies, since the immersive system provides an increased sense of manipulation, as well as the possibility of detailed inspection both inside and outside structures.

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A multi-agent system for optimizing physiological collection based on adaptive strategies

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Smart Health 2021年 19卷

作者： Aranda, Jorge Arthur Schneider Bavaresco, Rodrigo Simon da Silva Machado, Roger de Carvalho, Juliano Varella Corrêa, Adenauer Yamin Barbosa, Jorge Luis Victória Applied Computing Graduate Program (PPGCA) of University of Vale do Rio dos Sinos (UNISINOS) Av. Unisinos 950 São Leopoldo 93.022-750 RS Brazil Creative and Technological Sciences Institute of Feevale University ERS 239 2755 Novo Hamburgo RS 93525-075 RS Brazil Computer Science Graduate Program of Federal University of Pelotas Gomes Carneiro 1 Pelotas 96010-610 RS Brazil

Wearable devices have emerged from the evolution of communication and information technology, along with the miniaturization of electronic components. These devices monitor the user's physiology on a periodic basis and generally have low battery autonomy. This article proposes the Odin system, a multi-agent system that performs real-time analysis of physiological data in order to adapt the collection according to the user's health condition. Two types of adaptation were proposed in terms of adapting the collection. The first, wait-time adaptation (WTA), consists of collecting physiological data through a sensor defined as the main sensor, where the frequency of the collection is based on the user's condition. Meanwhile, the second, paused sensors adaptation (PSA), manages the activation status of secondary sensors when the main sensor suggests a possible risk to the user's health. An evaluation was implemented through two steps. First, a simulation was performed with requests control to optimize the parameters of the data collection. These results showed an increase of 214% in battery life in the adaptive scenario compared to one with no adaptivity. Second, Odin's adaptivity was evaluated in terms of a real dataset, which allowed for the reduction of the number of requests. This reduction optimized the battery consumption, with a 66% improvement over data collection with no adaptivity. © 2020 Elsevier Inc.

关键词： Adaptive systems Embedded systems Healthcare Wearable Devices

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FluxProg 2.0 - Teaching Introductory programming Using Flowcharts with Real and Simulated Robots for The Brazilian Robotics Olympiad (OBR)

FluxProg 2.0 - Teaching Introductory Programming Using Flowc...

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IEEE Latin American Robotics Symposium, LARS

作者： João Alberto Fabro Matheus Biscaya Gutierrez Fernando Henrique Ratusznei Caetano DAINF - Academic Department of Informatica PPGCA - Graduate Program on Applied Computing LASER-Laboratory for Advanced Robotics and Embedded Systems UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Information Systems academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Computer Engineering academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In this paper, an approach to aid in introductory programming courses is presented, focused on students that had never had any contact with computer programming. The approach, that was introduced in a previous paper [3], presents programming concepts using icons and “flowcharts”, and a 3D robotics simulator (CoppeliaSim), that has free educational use. This time, a real version of the simulated robot, built using Arduino and cheap, easily obtainable electronic components, is also presented. The programs to control the robot are developed by graphically constructing flowcharts on the visual editor, and then following the execution of programs using the simulated (or real) robot, step by step. This graphic program editor is named “FluxProg”, and its 2nd version is now available online, with new features comprising variables, arithmetic and logic expressions, thus providing a complete programming environment.

关键词： Flowcharts Visualization Three-dimensional displays Conferences Education Electronic components Robots

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