In this paper, we propose a novel framework for gait quality assessment based on imageanalysis, extending the traditional signal- based approach. Specifically, we construct Cycle Dissimilarity images (CDI) from raw g...
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ISBN:
(纸本)9798331541859;9798331541842
In this paper, we propose a novel framework for gait quality assessment based on imageanalysis, extending the traditional signal- based approach. Specifically, we construct Cycle Dissimilarity images (CDI) from raw gait signals. Such images summarize all local dissimilarities existing in the dynamics between a gait signal and one normal gait reference. Also, we construct a typical dissimilarity image, by matching each normal gait reference to itself. Then, we propose to quantify gait deviations by computing the distance between the CDIs and the typical dissimilarity images. Our results indicate that, compared to the signal-based approach, this new framework leads to a more precise gait deviation assessment, and a more refined characterization of motor impairments, as hemiparesis, tetraparesis, and paraparesis.
This research conducts a performance analysis on a real-time experimental multi-quadrature amplitude modulation (M-QAM) free-space optical (FSO) system under different fog conditions. The study focuses on experimental...
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ISBN:
(纸本)9798350348750;9798350348743
This research conducts a performance analysis on a real-time experimental multi-quadrature amplitude modulation (M-QAM) free-space optical (FSO) system under different fog conditions. The study focuses on experimental investigations to assess the system's tolerance and performance. Experimental results will contribute to a comprehensive understanding of the reliability aspects of the M-QAM FSO system, offering practical insights that are vital for real-world applications in challenging atmospheric conditions
Feature representations are the fundamental building blocks for various imageanalysis tasks like retrieval and classification. Traditionally, the Bag-of-Visual-Words (BoVW) framework has been a well-established appro...
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ISBN:
(纸本)9798350351491;9798350351484
Feature representations are the fundamental building blocks for various imageanalysis tasks like retrieval and classification. Traditionally, the Bag-of-Visual-Words (BoVW) framework has been a well-established approach for feature extraction. However, BoVW exhibits limitations in capturing the complex spectral-spatial relationships and fine-grained details within remote sensing images (RSIs). This paper proposes a novel deep learning approach that addresses these shortcomings and fits well with the BoVW framework for RSI analysis. Our method leverages a hybrid architecture that combines a Convolutional Neural Network (CNN) and a Graph Convolutional Network (GCN). The CNN extracts high-level spatial features from RSIs capturing prominent visual patterns and spatial arrangements within the image. These extracted features are then fed into the GCN, which operates on a graph structure constructed from the image data. The GCN excels at learning complex relationships between image elements based on their spatial proximity and spectral information. processing the CNN outputs through the GCN aims to extract and enhance the features that encapsulate both the spatial layout and the intricate spectral-spatial relationships within RSIs. This potentially translates to improved performance in various RSI analysis tasks that demand a nuanced understanding of the image content.
Polarimetric SAR calibration based on naturally distributed targets has been affected by the system signal-to-noise (SNR) level, the isolation level between polarimetric channels, and some algorithm processing factors...
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ISBN:
(纸本)9798350350920
Polarimetric SAR calibration based on naturally distributed targets has been affected by the system signal-to-noise (SNR) level, the isolation level between polarimetric channels, and some algorithm processing factors, which limit the data calibration accuracy and further degrade data interpretation applications. In this study, we conducted experiments on polarimetric calibration accuracies. The SNR level in the image and the crosstalk and imbalance distortion of the SAR system were experimentally analyzed to evaluate their effect on calibration accuracy. Simulated data and real data experiments have shown that polarimetric data calibration accuracy can be enhanced by a high image SNR and lower crosstalk between system channels. These studies can benefit the SAR system design, space-time variant distortion parameter measurement and correction for radar system maintenance, and requirement analysis for image data quality control and accuracy achievement.
Magnetic resonance imaging (MRI) is known as the gold standard for radiologists and clinicians for the diagnosis of different brain diseases. However, the images are often affected by low contrast which makes the inte...
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ISBN:
(纸本)9798350313345;9798350313338
Magnetic resonance imaging (MRI) is known as the gold standard for radiologists and clinicians for the diagnosis of different brain diseases. However, the images are often affected by low contrast which makes the interpretation and analysis difficult. In this paper, a novel image contrast enhancement method is proposed. The method relies on the decomposition of the image into squared eigen-functions of the 2D Schrodinger operator. The decomposition depends on a parameter gamma which controls the pixel intensity in the reconstruction. In addition, the method allows for filtering the noise simultaneously. The performance of the method is investigated on simulated and real images. The obtained results provide evidence for the feasibility and robustness of this method as a pre-processing tool for brain MRI images.
In this paper, we experimentally demonstrate the interference analysis of a non-line-of-sight (NLOS) multiple-input multiple-output (MIMO)-based optical camera communications (OCC) link. We propose an NLOS MIMO-OCC us...
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ISBN:
(纸本)9798350348750;9798350348743
In this paper, we experimentally demonstrate the interference analysis of a non-line-of-sight (NLOS) multiple-input multiple-output (MIMO)-based optical camera communications (OCC) link. We propose an NLOS MIMO-OCC using two organic light emitting diodes (OLEDs) and a camera as transmitters (Txs) and the receiver, respectively, as well as reflections from plain wall and paper surfaces. We analyze the performance of the proposed scheme when two OLED Txs are modulated out of phase and at different transmission frequencies f(s). We conduct an experimental investigation of the proposed system in an indoor environment and evaluate its performance in terms of signal-to-noise (SNR) ratio and the reception success rates R-rs with respect to camera exposure time, the analog gain and varying f(s). The initial results show that for a link span of 2 m, the reception success is 100 % for the SNR values of (i) similar to 5 dB at transmission frequencies of 100 and 200 Hz;and (ii) similar to 4 and similar to 6 dB for OLED1 and OLED2 at f(s1) and f(s2) of 100 and 200 Hz, respectively.
This study aims to enhance the efficiency of Visible Light Communication (VLC) channels and contribute to the reduction of carbon emissions in underground communications by leveraging Polar Codes and Multiresolution A...
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ISBN:
(纸本)9798350348750;9798350348743
This study aims to enhance the efficiency of Visible Light Communication (VLC) channels and contribute to the reduction of carbon emissions in underground communications by leveraging Polar Codes and Multiresolution analysis (MRA). It uses a specific configuration of frozen bits for the implementation of Polar codes. Additionally, it integrates the Daubechies Wavelet family with a five-level decomposition into the MRA filters. The effectiveness of these methodologies is evaluated separately, without incorporating additional techniques into the communication channel. The results depicted a significant improvement, around of 19 dB in channel performance. This represent a considerable reduction in carbon emissions in a underground copper production context.
This paper presents a comprehensive feasibility analysis designed to model Low Earth Orbit (LEO) satellite-to-ground communications for Quantum Key Distribution (QKD), focusing on the 1550nm wavelength to facilitate t...
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ISBN:
(纸本)9798350348750;9798350348743
This paper presents a comprehensive feasibility analysis designed to model Low Earth Orbit (LEO) satellite-to-ground communications for Quantum Key Distribution (QKD), focusing on the 1550nm wavelength to facilitate the distribution of information through fiber segments. Discrete Variable Decoy State Polarization-based BB84 protocol is assumed whereas various detection setups and environmental conditions are simulated. Our analysis focuses on the receiver's design in terms of aperture and focal length to deliver a general framework by examining the coupling efficiency, a parameter strongly affecting the QKD satellite downlink. Through detailed simulation, we identify optimal configurations and operational parameters for various receiver designs, significantly enhancing the efficiency and reliability of satellite-to-ground QKD systems. The findings offer promising directions for extending the range of QKD systems, potentially revolutionizing secure communications by integrating satellite-transmitted quantum keys with terrestrial fiber networks. This study not only underscores the feasibility of advancing satellite-to-ground QKD technology but also lays the groundwork for future innovations in global quantum communications infrastructure.
The main contribution lies in presenting an application of the Lanczos algorithm to provide an eigenbasis for a specific type of discrete Sine transform, referred to the signalprocessing literature as DST of type one...
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In this study, we present an unsupervised methodology for detecting moving targets using Capella Space's latest generation SAR sensor. The sensor has the capability to dwell on a target for an extended period of t...
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ISBN:
(纸本)9798350360332;9798350360325
In this study, we present an unsupervised methodology for detecting moving targets using Capella Space's latest generation SAR sensor. The sensor has the capability to dwell on a target for an extended period of time in its spotlight (SP) mode, which we take advantage of to track moving objects in an acquisition. An approach that combines a signal-processing-based workflow with an image-domain-based one is presented. From one side, the long-dwell SAR image is exploit by doing an interfeometric processing of different azimuth sub-apertures from the long-dwell. From another side, a kernelized cross correlation technique is used. By combining intermediate results from these complementary workflows, a smooth and robust track is obtained on the targets. The algorithm is demonstrated on a long-dwell spotlight obtained over a busy shipping channel with watercraft both small and large successfully tracked.
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