Titlebook: Geoinformatics and Data Analysis; Selected Proceedings Salah Bourennane,Petr Kubicek Conference proceedings 2022 The Editor(s) (if applicab

Confidential

https://doi.org/10.1007/978-3-642-92211-4re, rainfall data is analyzed using machine learning methods. The Machine Learning methods that used in this research are NN and LSTM. Based on the results of NN and LSTM, it can be concluded that the NN model is better than the LSTM model. This is due to the root mean square error (RMSE) value on the NN model is smaller than the LSTM model.

不能強(qiáng)迫我

Die elektrische Kraftübertragung support vector machine algorithm extraction results are the best, the overall accuracy is above 78%, and the Kappa is above 0.75; vegetation and field land is the main land type of Jiulong River Basin.

喪失

含水層

Comparative Study on Remote Sensing Image Classifier of Jiulong River Basin support vector machine algorithm extraction results are the best, the overall accuracy is above 78%, and the Kappa is above 0.75; vegetation and field land is the main land type of Jiulong River Basin.

遍及

L. Scharnweber,Otto Goldschmidtponent analysis (PCA) feature extraction, multiresolution segmentation and cell edges removal. Tests in our study area for this method showed an overall accuracy of 81.75%, outperformed the single NDVI used result (65.95%).

conference

Der elektrische Bau der Leitungsanlage,more accurate at predicting changes to building objects in spatial imagery. Notably, our proposed OSM-GAN architecture achieved over 88% accuracy predicting/detecting building object changes in high-resolution spatial imagery of Dublin city centre.

畢業(yè)典禮

Die elektrischen Erscheinungen des Gewittersthe software also can be supported. In this paper, we analyse how an automatic A/B testing can be realized in modern software development environments. We present an approach that supports long-term execution of A/B testing. We take advantage of widely-used CI/CD solutions and present an actual implementation.

泰然自若

無(wú)所不知

OSM-GAN: Using Generative Adversarial Networks for Detecting Change in High-Resolution Spatial Imagemore accurate at predicting changes to building objects in spatial imagery. Notably, our proposed OSM-GAN architecture achieved over 88% accuracy predicting/detecting building object changes in high-resolution spatial imagery of Dublin city centre.

弓箭

A/B Testing via?Continuous Integration and?Continuous Deliverythe software also can be supported. In this paper, we analyse how an automatic A/B testing can be realized in modern software development environments. We present an approach that supports long-term execution of A/B testing. We take advantage of widely-used CI/CD solutions and present an actual implementation.