Automation is playing an increasing role in the field of quality assurance. For the visual inspection of larger assemblies such as aircraft fuselages or ship hulls, the use of UAVs is an option. This paper deals with ...
Automation is playing an increasing role in the field of quality assurance. For the visual inspection of larger assemblies such as aircraft fuselages or ship hulls, the use of UAVs is an option. This paper deals with one aspect of the UAV-supported inspection of assemblies in production. Here, newly added components have to be checked for correct assembly. The planning of the shortest possible route from which all components to be inspected can be viewed as well as the estimation of the UAV’s position relative to the component have already been presented in previous work. We propose strategies that can be used if an inspection point cannot be reached by the UAV or the component to be inspected cannot be seen by the UAV’s camera from the inspection point. For this purpose, we generate alternative inspection points that can be used if errors occur during the inspection from the original inspection point. To achieve this, we present a metric that can be used to select an alternative inspection point that is as suitable as possible. We conclude by demonstrating how this strategy works by evoking different failure cases in a simulated environment.
Facial expression recognition(FER)remains a hot research area among computer vision researchers and still becomes a challenge because of high intraclass *** techniques for this problem depend on hand-crafted features,...
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Facial expression recognition(FER)remains a hot research area among computer vision researchers and still becomes a challenge because of high intraclass *** techniques for this problem depend on hand-crafted features,namely,LBP,SIFT,and HOG,along with that a classifier trained on a database of videos or *** execute perform well on image datasets captured in a controlled condition;however not perform well in the more challenging dataset,which has partial faces and image ***,many studies presented an endwise structure for facial expression recognition by utilizing DL ***,this study develops an earthworm optimization with an improved SqueezeNet-based FER(EWOISN-FER)*** presented EWOISN-FER model primarily applies the contrast-limited adaptive histogram equalization(CLAHE)technique as a pre-processing *** addition,the improved SqueezeNet model is exploited to derive an optimal set of feature vectors,and the hyperparameter tuning process is performed by the stochastic gradient boosting(SGB)***,EWO with sparse autoencoder(SAE)is employed for the FER process,and the EWO algorithm appropriately chooses the SAE ***-ranging experimental analysis is carried out to examine the performance of the proposed *** experimental outcomes indicate the supremacy of the presented EWOISN-FER technique.
Designing multi-agent systems with safety constraints and uncertain dynamics is a challenging problem. This paper studies a stochastic dynamic noncooperative game with coupling safety chance constraints. The uncertain...
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Crime forecasting is a critical endeavor aimed at preventing future criminal actions, specifically the rising rate of violence against women in India. This study proposes the model to predict crimes committed against ...
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ISBN:
(数字)9798331521691
ISBN:
(纸本)9798331521707
Crime forecasting is a critical endeavor aimed at preventing future criminal actions, specifically the rising rate of violence against women in India. This study proposes the model to predict crimes committed against women using data from the National Crime Records Bureau's (NCRB) monthly crime report. The dataset encompasses district and state-wise crime activities from 2001 to 2014. The proposed work objectives are identifying factors influencing these crimes and developing predictive models using machine learning (ML). The study employs Exploratory Data Analysis (EDA), to enhance the predictive power of the models. The suggested study uses XGBoost, Random Forest (RF), and Neural Network (NN). The neural network algorithm outperforms the Random Forest and XGBoost techniques among these three. The Random Forest algorithm has the worst performance. After comparing the accuracies of various methods, such as XGBoost (92%), and Random Forest (89.84%) classifiers using imbalanced datasets (without employing Synthetic Minority Oversampling Technique (SMOTE) technique), it was found that the neural network algorithm (95.81%) delivers the highest accuracy. This study looks at model accuracies and finds that, after applying the SMOTE algorithm, neural network algorithms performed best, with an accuracy of 96.76%, outperforming the accuracies of the remaining models, which included the Random Forest (93.08%) and XG-Boost (95%).
Tropical cyclones, characterized by strong winds and heavy rainfall, threaten human life in coastal regions crucial to the economy, including fisheries, agriculture, tourism, and infrastructure. Their frequent occurre...
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ISBN:
(数字)9798331528171
ISBN:
(纸本)9798331528188
Tropical cyclones, characterized by strong winds and heavy rainfall, threaten human life in coastal regions crucial to the economy, including fisheries, agriculture, tourism, and infrastructure. Their frequent occurrence impacts communities reliant on these industries for livelihoods. Accurate estimation of tropical cyclone intensity is vital for disaster preparedness, risk assessment, and timely evacuations. Recent advancements in machine learning and deep learning have been applied to predict cyclone intensity from satellite images, providing insights into cyclone dynamics and enhancing disaster response. This paper analyzes recent research on intensity estimation using various machine learning algorithms and discusses future prospects for improving accuracy and reliability.
Personality recognition is of great significance in deepening the understanding of social relations. While personality recognition methods have made significant strides in recent years, the challenge of heterogeneity ...
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In Spoken Language Understanding (SLU) the task is to extract important information from audio commands, like the intent of what a user wants the system to do and special entities like locations or numbers. This paper...
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Attention management in software development proves to be a highly relevant issue. It offers various ways of managing the user's attention using visual perception of the work environment. Awareness of the workplac...
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ISBN:
(数字)9798350353433
ISBN:
(纸本)9798350353440
Attention management in software development proves to be a highly relevant issue. It offers various ways of managing the user's attention using visual perception of the work environment. Awareness of the workplace provides a user with work context which may positively affect the productivity and workflow of a project. However, the work context may also provide the user with arbitrary information. Thus, regulations of incoming workplace information are required throughout the user's work cycle. Furthermore, previous research supports the proposed extensions devised according to the lacking parts in the existing project management system. Furthermore, to stabilize the extensions, results from an experiment conducted on the proof-of-concept designed according to the proposed parts.
Model transformations are used in different areas of computer science. They are often used during the development of software but also at runtime, e.g., to update a digital twin. However, users of these languages stil...
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