Although multispectral pedestrian detection studies have shown remarkable detection performances, they are still vulnerable to adversarial attacks. We see the similarity relations between object candidates were not ma...
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Although multispectral pedestrian detection studies have shown remarkable detection performances, they are still vulnerable to adversarial attacks. We see the similarity relations between object candidates were not maintained because of the adversarial attacks, resulting in performance degradation. In this paper, we introduce a new method that can preserve the similarity relation between candidates against adversarial attacks using multispectral knowledge. First, we propose Similarity Relation Generation (SRG) module to generate the optimal similarity relation between clean candidates by referring to the two modalities (color and thermal). Second, we propose Adversarial Similarity Relation Preserving (ASRP) module to guide the similarity relation between adversarial candidates to be similar to that of the clean candidates. By maintaining the relationship between candidates, our multispectral detector can distinguish between pedestrian/background classes even in adversarial attacks. Comprehensive experimental results show that our method conspicuously improves the adversarial robustness.
The rise of 5G technology has revolutionized wireless communication, ushering in a new era of unparalleled connectivity. Approaching Beyond 5G networks, Software Defined Networks have emerged as a promising paradigm t...
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ISBN:
(数字)9798350370997
ISBN:
(纸本)9798350371000
The rise of 5G technology has revolutionized wireless communication, ushering in a new era of unparalleled connectivity. Approaching Beyond 5G networks, Software Defined Networks have emerged as a promising paradigm to enhance flexibility and scalability in cellular networks. However, the challenge of 5G is to ensure the network's performance based on the different Quality of Service requirements for offering interactive services. Proactive detection of anomalies can significantly improve network performance. To address this issue, we present AnDet, a robust ML-based model specifically designed for anomaly detection in SDN-enabled B5G cellular networks. Next, we deploy the proposed AnDet for anomaly detection on SDN-enabled B5G cellular networks, enhancing overall network performance and reliability. Moreover, we incorporate Explainable AI approaches into the AnDet model to ensure transparency and interpretability. Finally, we capture different performance metrics for models and deployments to evaluate the proposed solution. The extensive simulation results show that AnDet effectively identifies anomalies in SDN-enabled cellular networks operating in B5G environments, achieving an impressive 97.2% accuracy in anomaly detection.
This paper presents a advance approach for ship detection in satellite imagery utilizing a modified DeepLabV3+ architecture, specifically designed to overcome the challenges inherent in such data. The proposed model f...
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ISBN:
(数字)9798350379716
ISBN:
(纸本)9798350379723
This paper presents a advance approach for ship detection in satellite imagery utilizing a modified DeepLabV3+ architecture, specifically designed to overcome the challenges inherent in such data. The proposed model features an enhanced feature extraction process and a refined atrous spatial pyramid pooling (ASPP) module, which together improve the detection of ships across various sizes and shapes. Comprehensive experiments on publicly available satellite datasets reveal that the modified DeepLabV3+ significantly outperforms existing state-of-the-art methods, achieving an accuracy of 98%. These findings demonstrate the model's robust ability to identify and localize ships in complex maritime settings, offering promising potential for improved maritime situational awareness and operational efficiency.
Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process,...
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This paper presents a composable machine learning method for generalizing the quality-of-transmission (QoT) metric estimation in optical networks. The composable machine learning approach characterizes this metric for...
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The DR becomes increasingly common, there is a need to automatically extract and classify disease severity. Due to diabetes problems, about 2% of people with this disease become completely blind, and DR complications ...
The DR becomes increasingly common, there is a need to automatically extract and classify disease severity. Due to diabetes problems, about 2% of people with this disease become completely blind, and DR complications make him 10% visually impaired if he has diabetes for 15 years. Furthermore, it plays an important role in the progression of blindness in middle-aged and older adults. If the disease is not recognized as soon as possible, patients can experience a severe stage of irreversible blindness. The shortage of ophthalmologists is a serious problem for the growing number of diabetic patients. Hard exudates must be found to screen and assist in disease monitoring and diagnosis. Therefore, Lloyd's clustering technique was used in this work.
In recent years, software engineers have explored ways to assist quantum software programmers. Our goal in this paper is to continue this exploration and see if quantum software programmers deal with some problems pla...
In recent years, software engineers have explored ways to assist quantum software programmers. Our goal in this paper is to continue this exploration and see if quantum software programmers deal with some problems plaguing classical programs. Specifically, we examine whether intermittently failing tests, i.e., flaky tests, affect quantum software development. To explore flakiness, we conduct a preliminary analysis of 14 quantum software repositories. Then, we identify flaky tests and categorize their causes and methods of fixing them. We find flaky tests in 12 out of 14 quantum software repositories. In these 12 repositories, the lower boundary of the percentage of issues related to flaky tests ranges between 0.26% and 1.85% per repository. We identify 46 distinct flaky test reports with 8 groups of causes and 7 common solutions. Further, we notice that quantum programmers are not using some of the recent flaky test countermeasures developed by software engineers. This work may interest practitioners, as it provides useful insight into the resolution of flaky tests in quantum programs. Researchers may also find the paper helpful as it offers quantitative data on flaky tests in quantum software and points to new research opportunities.
This study deals with the coordination of surge protection devices (SPD) in photovoltaic systems (PV). A PV farm model was developed in MATLAB Simulink with all the main components, solar panels, converter, grounding ...
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ISBN:
(数字)9798350388107
ISBN:
(纸本)9798350388114
This study deals with the coordination of surge protection devices (SPD) in photovoltaic systems (PV). A PV farm model was developed in MATLAB Simulink with all the main components, solar panels, converter, grounding system, power transformer, cables in the DC and AC branches with their capacitances, and surge protection device throughout the installation. It was found that when lightning strikes the grounding system or in the vicinity of the PV installation, the coordination among SPD types 1, 2, and 3 is lost. Miscoordination can cause damage to several elements of the PV system, mainly the inverters. Finally, solutions were proposed to avoid SPD miscoordination during lightning strikes.
Power quality challenges have generated a lot of disputes between utilities,customers,network operators,and equipment manufacturers around the world as regards the share of responsibility for power quality solutions,t...
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Power quality challenges have generated a lot of disputes between utilities,customers,network operators,and equipment manufacturers around the world as regards the share of responsibility for power quality solutions,this results in different levels of financial and technical losses for both the network operators and the *** of the major consequences of the operation of heavy-duty factories globally is the corruption of power quality at the point of common coupling(PCC).In order to quantify the harmonics contribution at the PCC by industrial consumers,this paper presents three-phase total harmonics distortion of current(THDi)prediction model at the *** proposed artificial neural network(ANN)models use a multilayer perceptron neural network(MLPN)to predict three-phase total harmonic *** input parameter used in the models is easily measured with basic power *** model was trained with input parameters captured at 33 kV and 132 kV voltage levels using power quality meters at five(5)different steel manufacturing ***(8)different models were designed,trained,validated,and tested with different combinations of input parameters,number of hidden layers,and number of neurons in the hidden *** results show that the model with two hidden layers which uses four major power parameters(Current,apparent power,reactive and active power)as input parameters in the training model had the best performance with a 95.5%coefficient of correlation between the measured THDi and the predicted THDi.
The prevalence of DR is steadily rising, which necessitates the automatic disease severity extraction and classification. About 2% of those with this illness are entirely blind because of the diabetic mellitus problem...
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The prevalence of DR is steadily rising, which necessitates the automatic disease severity extraction and classification. About 2% of those with this illness are entirely blind because of the diabetic mellitus problem and 10% get vision impairment after 15 years of diabetes as a result of the DR complication. It is also a significant contributor to blindness in both middle aged and older age groups. The patient may develop to severe stages of irreversible blindness if the condition is not detected early. The growing number of diabetic patients face a major issue due to a lack of ophthalmologists. It is suggested that an automated DR screening system be created to aid the ophthalmologist in making decisions. One of the primary symptoms of the DR is hard exudates. The detection of hard exudates is crucial for screening purposes and aids in disease monitoring and diagnosis. Thus, utilising Lloyd’s clustering technique, this work offered a unique techniques to segment the exudates and irregularities in DR were found.
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