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Titlebook: Next Generation Data Science; Second Southwest Dat Henry Han,Erich Baker Conference proceedings 2024 The Editor(s) (if applicable) and The

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發(fā)表于 2025-3-25 06:54:14 | 只看該作者
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發(fā)表于 2025-3-25 08:30:59 | 只看該作者
Online Linear Regression Based on?Weighted Averagent storage space and recalculating the model to account for the new data. On-line learning addresses these issues by incrementally modifying the model as data is encountered, and then discarding the data. In this study we introduce a new online linear regression approach. Our approach combines newly
23#
發(fā)表于 2025-3-25 12:43:50 | 只看該作者
Dimension Reduction Stacking for?Deep Solar Wind Clusteringsult of various processes such as ionization and acceleration occur in the inner corona. Machine learning methods have been successful in characterizing solar wind in-situ observations using unsupervised deep clustering and dimensionality reduction techniques, but it remains unclear as to how solar
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發(fā)表于 2025-3-25 17:15:21 | 只看該作者
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發(fā)表于 2025-3-25 23:50:54 | 只看該作者
26#
發(fā)表于 2025-3-26 01:05:17 | 只看該作者
A Scene Tibetan Text Detection by Combining Multi-scale and Dual-Channel Featuresbetan cultural heritage. However, recognizing Tibetan text in natural scene images is a challenging task due to factors such as variable fonts, complex backgrounds, and poor imaging conditions. In this study, we present a novel approach called Multi-Scale Dual-Channel Feature Fusion (MDFF) for Tibet
27#
發(fā)表于 2025-3-26 05:13:27 | 只看該作者
28#
發(fā)表于 2025-3-26 10:11:18 | 只看該作者
A Comparative Evaluation of?Image Caption Synthesis Using Deep Neural Networkoviding appropriate captions. In this study, we aimed to evaluate and compare the performance of two different model architectures using pre-trained CNN models for image classification and sequential LSTM models for caption generation. Specifically, we used RestNet50 and inceptionV3 CNN models with
29#
發(fā)表于 2025-3-26 15:48:44 | 只看該作者
Parameter Estimation in?Biochemical Models Using Marginal Probabilitiesnterest. We formulate the objective function through a fitting scheme based on a maximum likelihood estimator (MLE) that uses the marginal distribution of the species involved, which is a new way not attempted before. The quality of the method is evaluated for some example models, such as the Michae
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發(fā)表于 2025-3-26 19:25:14 | 只看該作者
Detecting Microservice Anti-patterns Using Interactive Service Call Graphs: Effort Assessmentls supporting effective anti-pattern detection is limited. Though involving the human in the loop is useful, it is time-consuming and lacks the accuracy necessary to complete such a task. For such a purpose, we consider visualizing the microservice system architecture using the service view, specifi
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