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2023 Laser Science, LS 2023

作者： Gül, G. On, M. Berkay Singh, S.K. Proietti, R. Kanter, G.S. Yoo, S.J.B. Kumar, P. Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Department of Electronics and Communication Eng. Indian Institute of Technology Roorkee247667 India Department of Electronics and Telecommunications Engineering Politecnico di Torino Italy Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

We investigate the impact of wavelength choice for the classical headers in quantum wrapper networking with O-band quantum payload. We show that a C-band header performs substantially better than an O-band header. ... 详细信息

关键词： Quantum electronics

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GraCo: Granularity-Controllable Interactive Segmentation

arXiv

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arXiv 2024年

作者： Zhao, Yian Li, Kehan Cheng, Zesen Qiao, Pengchong Zheng, Xiawu Ji, Rongrong Liu, Chang Yuan, Li Chen, Jie School of Electronic and Computer Engineering Peking University Shenzhen China Peng Cheng Laboratory Shenzhen China -Preferred Program Peking University Shenzhen Graduate School China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China Department of Automation and BNRist Tsinghua University Beijing China

Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity output and multi-granularity output. The latter aims to alleviate the spatial ambiguity present in the former. However, the multi-granularity output pipeline suffers from limited interaction flexibility and produces redundant results. In this work, we introduce Granularity-Controllable Interactive Segmentation (GraCo), a novel approach that allows precise control of prediction granularity by introducing additional parameters to input. This enhances the customization of the interactive system and eliminates redundancy while resolving ambiguity. Nevertheless, the exorbitant cost of annotating multi-granularity masks and the lack of available datasets with granularity annotations make it difficult for models to acquire the necessary guidance to control output granularity. To address this problem, we design an any-granularity mask generator that exploits the semantic property of the pre-trained IS model to automatically generate abundant mask-granularity pairs without requiring additional manual annotation. Based on these pairs, we propose a granularity-controllable learning strategy that efficiently imparts the granularity controllability to the IS model. Extensive experiments on intricate scenarios at object and part levels demonstrate that our GraCo has significant advantages over previous methods. This highlights the potential of GraCo to be a flexible annotation tool, capable of adapting to diverse segmentation scenarios. The project page: https://***/GraCo. Copyright © 2024, The Authors. All rights reserved.

关键词： Pipelines

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Classifying Ore Deposits Based on La-Icp-Ms Geochemistry of Natural Gold

SSRN

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SSRN 2024年

作者： Verbel, Angel Augusto Schutesky, Maria Emilia Gregory, Daniel D. Verbel, Arturo University of Brasilia Institute of Geosciences Graduate Program in Geology DF Brasília70910-900 Brazil University of Toronto Department of Earth Sciences TorontoONM5S 3B1 Canada Universidad de los Andes Systems and Computing Engineering Department School of Engineering Bogotá111711 Colombia

Systematic sampling of gold grains and their characterization in abundance and morphology can be used as a vectoring tool for mineral deposits. However, the processes that lead to the formation of an ore deposit are multiscale and nonlinear. As a result, the elemental compositions recorded in gold grains during the mineralization process seem mostly irregular and unpredictable. Here, we took advantage of the capabilities of neural networks to approximate, a natural nonlinear function that better explains the chemical variability observed in gold allowing us to make predictions. this was achieved by using published data of trace elements in gold of four types of gold deposits (i.e., Orogenic, VMS, porphyry and epithermal) from 47 different localities, obtained by laser ablation-inductively coupled plasma-mass spectrometry (LA- ICP-MS). The model was optimized by training five different architectures on the most influential elements, determined by principal component analysis (PCA). As a result, it was found that two hidden layers with 10 neurons each, is the best architecture for using trace elements as predictors of the type of deposit that formed a natural gold grain. In order to encourage the use of the findings made in this paper, we introduce OreGenes, an app developed in Matlab2023b based on the best-obtained model. It allows any user who possesses compatible data, the ability to import and process it to obtain a prediction with an average accuracy level of 88.9% confidence to determine the mineral deposit type that an unknown gold grain came from which grants the user the ability to have a powerful tool for exploration or research. © 2024, The Authors. All rights reserved.

关键词： Deposits

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Evaluation of convolutional neural networks for COVID-19 classification on chest X-rays

arXiv

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arXiv 2021年

作者： Zeiser, Felipe André Da Costa, Cristiano André De Oliveira Ramos, Gabriel Bohn, Henrique Santos, Ismael Da Rosa Righi, Rodrigo Graduate Program in Applied Computing Universidade Do Vale Do Rio Dos Sinos São Leopoldo Brazil

Early identification of patients with COVID-19 is essential to enable adequate treatment and to reduce the burden on the health system. The gold standard for COVID-19 detection is the use of RT-PCR tests. However, due to the high demand for tests, these can take days or even weeks in some regions of Brazil. Thus, an alternative for detecting COVID-19 is the analysis of Digital Chest X-rays (XR). Changes due to COVID-19 can be detected in XR, even in asymptomatic patients. In this context, models based on deep learning have great potential to be used as support systems for diagnosis or as screening tools. In this paper, we propose the evaluation of convolutional neural networks to identify pneumonia due to COVID-19 in XR. The proposed methodology consists of a preprocessing step of the XR, data augmentation, and classification by the convolutional architectures DenseNet121, InceptionResNetV2, InceptionV3, MovileNetV2, ResNet50, and VGG16 pre-trained with the ImageNet dataset. The obtained results demonstrate that the VGG16 architecture obtained superior performance in the classification of XR for the evaluation metrics using the methodology proposed in this article. The obtained results for our methodology demonstrate that the VGG16 architecture presented a superior performance in the classification of XR, with an Accuracy of 85.11%, Sensitivity of 85.25%, Specificity of 85.16%, F1-score of 85.03%, and an AUC of 0.9758. © 2021, CC BY-NC-SA.

关键词： Convolutional neural networks

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Vision of the Seas: Open Visual Perception Framework for Autonomous Sailing Vessels

Vision of the Seas: Open Visual Perception Framework for Aut...

引用

International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Araújo André P. D. Ganadev Prajapathy Chandrasekharan Esteban Walter Gonzalez Clua Phillipe Preux Eduardo Charles Vasconcellos Luiz Marcos Garcia Gonçalves Institute of Computing Universidade Federal Fluminense Niteroi Brazil Inria Université de Lille Villeneuve d’Ascq France Elec. and Comp. Eng. Graduate Program Univ. Fed. do Rio Grande do Norte Natal Brazil

We propose an Open Visual Perception framework for autonomous navigation and obstacle detection in marine sailing vessels. The proposed framework lays the groundwork for perceiving marine objects needed for vessel navigation and obstacle avoidance using only image processing as the primary method. Various methods are explored to extract features such as waterline, terrain, and other vessels. The proposed framework also incorporates image stabilization techniques without the need for an Inertial Measurement Unit to compensate for ocean wave oscillations. The work also introduces the system architecture of an autonomous marine vessel, besides the components of the open visual perception framework. Results demonstrate the capabilities of obstacle detection, horizon line identification, and water texture detection.

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Assisted Multi-Frame Approach for Super-Resolution in UAV Photogrammetric Images

Assisted Multi-Frame Approach for Super-Resolution in UAV Ph...

引用

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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Low-Complexity HEVC Transrating Based on Prediction Unit Mode Inheritance

Low-Complexity HEVC Transrating Based on Prediction Unit Mod...

引用

European Signal Processing Conference (EUSIPCO)

作者： Matheus Lindino Thiago Bubolz Bruno Zatt Daniel Palomino Guilherme Correa Video Technology Research Group (ViTech) Graduate Program in Computing (PPGC) Federal University of Pelotas (UFPel) Pelotas Brazil

ISBN: (数字)9789082797053

ISBN: (纸本)9781728150017

Video transcoding for bit rate adaptation has become mandatory for over-the-top applications that deliver multimedia content in heterogeneous environments under different network conditions and user capabilities. As transcoding requires sequentially decoding and re-encoding the video bitstream, the computational cost involved in the process is too high, especially when considering current state-of-the-art codecs, such as the High Efficiency Video Coding (HEVC). This work presents a fast HEVC transcoder for bit rate adaptation based on Prediction Unit (PU) mode inheritance, which uses information gathered from the HEVC decoding process to accelerate PU mode decision in the re-encoding process. Experimental results show that the proposed method achieves an average transrating time reduction of 42% at the cost of a bitrate increase of 0.54%.

关键词： Statistical analysis Bit rate Transcoding Streaming media Decoding Complexity theory High efficiency video coding

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Assistive technology with device for self-inflating bag in neonatology

引用

Research on Biomedical Engineering 2025年第2期41卷

作者： Marcelino, Ana Carolina Rodovanski, Giovana Pascoali Bonetti, Karoline Panes, Caio Rabinovich de Almeida Martins, Fernando Moran, Cristiane Aparecida Araranguá Brazil Graduate Program in Neurosciences and Behavior Department of Experimental Psychology of the Institute of Psychology-University of São Paulo Sao Paulo Brazil Araranguá Brazil Computer Engineering Instituto Mauá de Tecnologia São Caetano do Sul Brazil Electronic Engineering and Computing with Emphasis on Electronic Devices and Systems at Instituto Tecnológico de Aeronáutica–ITA São Caetano do Sul Brazil Department of Physiotheraphy and at the Postgraduate Program in Rehabilitation Science of the Federal University of Santa Catarina-UFCS Ararangua Brazil

Purpose: The objectives of this study were to create a device with technological development of the self-inflating bag (SIB) equipment to measure the variables tidal volume, peak inspiratory pressure, and inspiratory flow and to evaluate the knowledge of undergraduate students in handling the SIB. To reduce the risks of mortality, length of hospital stay, and infections, SIB is a resource used to ventilate the patient through the inflation of the device, but it is not capable of measuring the ventilatory parameters. Excess ventilation and incorrect handling of the bag can cause lung injury in newborns. Therefore, measuring these parameters can prevent lung injury resulting from inadequate ventilation. Method: This is a cross-sectional and experimental study, with the development of a device SIB that allows the evaluation of variables of neonatal respiratory mechanics that were tested with an artificial lung. It was approved by the Research Ethics Committee and the research was developed in three stages: the first represents the search for scientific articles for the consensus of neonatal ventilatory variables for the construction of the SIB parameters;the second stage depicts the technological development of a device capable of monitoring such variables through the SIB. In the third stage, the content validation of the device with the handling of the SIB was carried out by students of medicine and physiotherapy courses of Brazil. Results: In this work, a device that analyzes the values of the main ventilatory parameters in neonatology was developed and to generate a safety range for the use of the device, curves with a tolerance of 10% up and down were created. All electronic components were coupled to the equipment, with a display that transmits the parameter values. The web page can be used on a cell phone, tablet, computer, or SmartTv, as long as it is connected to the "RespiratorIoT_AP" network. Among the 29 participants in the study, 8 said they were familiar w

关键词： Students

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Hardware Architecture for the Regular Interpolation Filter of the AV1 Video Coding Standard

Hardware Architecture for the Regular Interpolation Filter o...

引用

European Signal Processing Conference (EUSIPCO)

作者： Daiane Freitas Rafael da Silva Ícaro Siqueira Cláudio M. Diniz Ricardo A. L. Reis Mateus Grellert Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil Graduate Program on Microelectronics Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Embedded Computing Lab Federal University of Santa Catarina (UFSC) Florianopólis Brazil

ISBN: (数字)9789082797053

ISBN: (纸本)9781728150017

This work proposes a hardware architecture for fractional-pixel interpolation filter defined in the royalty-free AV1 video coding standard. Analysis conducted in this work shows that the AV1 Regular family of filters has the highest usage especially when considering high resolution videos. The proposed architecture implements the 15 interpolation filters of the AV1 Regular family and is capable to interpolate videos of up to 8K video resolution at 120 fps. The proposed architecture achieves the highest throughput compared to related works.

关键词： Video coding Interpolation Computer architecture Parallel processing Filtering algorithms Hardware Standards

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Evaluating a New Approach to Data Fusion in Wearable Physiological Sensors for Stress Monitoring 9th

Evaluating a New Approach to Data Fusion in Wearable Physiol...

引用

9th Brazilian Conference on Intelligent Systems, BRACIS 2020

作者： Rodrigues, Clarissa Fröhlich, William R. Jabroski, Amanda G. Rigo, Sandro J. Rodrigues, Andreia de Castro, Elisa Kern Applied Computing Graduate Program UNISINOS São Leopoldo Brazil São Leopoldo Brazil Universidade Lusíada Lisboa Portugal

ISBN: (纸本)9783030613792

The physiological signs are a reliable source to identify stress states, and wearable sensors provide precise identification of physiological signs associated with the stress occurrence. The literature review shows that the use of physiological signs as a source for stress patterns identification is still a critical investigation subject. Few studies evaluate the effect of combining several different signals and the implications of the data acquisition procedures and details. This article’s objective is to investigate the possible integration of data obtained from heart rate variability, electrocardiographic, electrodermal activity, and electromyography to detect stress patterns, considering a new experimental protocol to data acquisition. The data acquisition involved the Trier Social Stress Test, wearable sensor monitoring, and complementary stress perception instruments, resulting in a publicly available dataset. This dataset was evaluated using different machine learning classifiers, considering the obtained annotated data and exploring different physiological features and their combinations. © 2020, Springer Nature Switzerland AG.

关键词： Data acquisition

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