3D human pose estimation (HPE) has improved significantly through Graph Convolutional Networks (GCNs), which effectively model body part ***, GCNs have limitations, including uniform feature transformations across nod...
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programming can help K-12 students to develop their 21st-century core skills. Despite the benefits, programming is not common to be delivered in Indonesian K-12 education. There is a need to understand potential chall...
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This paper presents an approach to analyze clusters as a means to determine the characteristics of strength training motion patterns. The proposed method emphasizes the observation of dominance sequences within cluste...
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It can be argued that the Convolutional Neural Network (CNN) used in this research is an efficient algorithm for classifying images based on the end prediction of the path taken. In every plot that is made, there is a...
It can be argued that the Convolutional Neural Network (CNN) used in this research is an efficient algorithm for classifying images based on the end prediction of the path taken. In every plot that is made, there is a similar process for achieving a prediction of the final result. The implementation for each of these procedures follows the steps that are summarized into a flow of analysis stages that can help to develop the application of an algorithm. The initial stage is to take the handwriting from the user which is then pre-processed the image, to eliminate existing noise, and sharpen the contrast, so that the image can be seen clearly. Images will be processed and analyzed using the Convolutional Neural Network model, training will be carried out, with an average training of a dataset of 100 epochs or about 7 to 10 minutes, and labeling on the trained dataset. The accuracy of the training reached 98.89%, as a proportion of the different characteristics of the handwriting sample.
Adaptive Mesh Refinement (AMR) is a widely known technique to adapt the accuracy of a solution in critical areas of the problem domain instead of using regular or irregular but static meshes. The MARE2DEM is a paralle...
Adaptive Mesh Refinement (AMR) is a widely known technique to adapt the accuracy of a solution in critical areas of the problem domain instead of using regular or irregular but static meshes. The MARE2DEM is a parallel application that employs the AMR technique to model 2D electromagnetics in oil and gas exploration. The modeling consists in iteratively applying a data inversion based on a set of measurements collected and registered by a survey on an area of interest. The parallelism of the MARE2DEM works by dividing the workload into a set of refinement groups that represent overlapping areas of the problem domain. Each refinement group can be computed independently of the others by a set of workers, carrying out the AMR in the meshes when necessary. The shape and compute performance of the refinement group depend directly of a set of user-defined parameters. In this article, we provide a method to estimate the MARE2DEM performance for all possible values that can be used in the influencing parameters of the application for a given case study. Our relatively cheap method enables the geologist to configure MARE2DEM correctly and extract the best performance for a given cluster configuration. We detail how the method works and evaluate its effectiveness with success, pinpointing the best values for the creating refinement groups using a real case study from the Marlim field on the coast of Rio de Janeiro, Brazil. Although we demonstrate our evaluation with this scenario, our method works for any input of MARE2DEM.
computer vision has been used in many areas such as medical, transportation, military, geography, etc. The fast development of sensor devices inside camera and satellite provides not only red-greed-blue (RGB) images b...
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The success of machine learning models relies heavily on effectively representing high-dimensional data. However, ensuring data representations capture human-understandable concepts remains difficult, often requiring ...
Understanding temporal relationships in text from electronic health records can be valuable for many important downstream clinical applications. Since Clinical TempEval 2017, there has been little work on end-to-end s...
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Widyaiswara is required to show the best performance to fulfill his duties and obligations. Therefore, it is very important to measure the performance of the Widyaiswara, so that it can be used as evaluation material ...
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Sasirangan cloth is one of the traditional cloths owned by Indonesia and is a typical cloth originating from the province of South Kalimantan. This Sasirangan cloth has many motifs and is unique. Sasirangan cloth is a...
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