Representing and reconstructing large-scale scenes, such as those found in aerial imagery, presents significant challenges due to the inherent scalability limitations of training a single NeRF. To address these issues, we propose BirdNeRF, a…
Category: 7. Maths
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Dance classification using pretrained deep learning models integrated with the circular Fermatean fuzzy MARCOS method
This section discusses the basic concept related to CFFS and proposes the CFF-MARCOS approach. Abbreviation section shows the list of symbols with their description.
Definition 1:
Ref19. Consider a fixed universe
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A method for instrumental seismic intensity assessment in Western China based on RF and MLP
Establishing a reliable seismic intensity assessment model relies on the development of a predictive model that accurately captures the input–output relationship. Utilizing the selected ground motion parameters and data samples, this paper…
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Building sensor coverage in couture: balancing cost, coverage, and comfort
ILP is a mathematical optimization technique in which decision variables must take integer values. It has been one of the most widely used approaches for solving equipment layout and location optimization problems. ILP is well-suited to handling…
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Automating wastewater characteristic parameter quantitation using neural architecture search in AutoML systems on spectral reflectance data
Experimental conditions
This work focuses on predicting wastewater characteristics using a dataset proposed by the authors of14. The dataset includes various influent wastewater parameters, and the study aims to predict key characterization…
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Fatigue crack propagation analysis considering the dynamic crack-load coupling effect
Yu, W. & Mechefske, C. K. A new model for the single mesh stiffness calculation of helical gears using the slicing principle. Iran. J. Sci. Technol. Trans. Mech. Eng. 43, 503–515 (2019).
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A forest fire identification and monitoring model based on improved YOLOv8
The experimental process is mainly divided into three stages: dataset generation, model training and target detection, as shown in Fig. 10:
Fig. 10 Flowchart of experiments and tests.
Dataset and preprocessing
In this study, a comprehensive…
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Machine learning models for mechanical properties prediction of basalt fiber-reinforced concrete incorporating graphical user interface
ML models’ prediction performance
Figure 5 displays the bar normal distribution of errors produced by five machine learning models (SVR, BR, RFR, DT, and GBR) during the test and train phases of predicting the CS value of BFRC. It shows that…
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A digital twin framework for urban parking management and mobility forecasting
This section presents the key points, describes the data used, analyzes the various available sources, and illustrates the data fusion process. A detailed description of the methods and models used to develop the DT framework is then provided….
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