Machine learningLUCASDigital soil mapping (DSM) techniques are widely employed to generate soil maps. Soil properties are typically predicted individually, while ignoring the interrelation between them. Models for predicting multiple properties exist, but they are computationally demanding and often fail to...
June-1, July-1, and August-1, respectively. Panelse–hillustrate equivalent observation probabilities for 2060, assuming the emission scenario RCP4.5. Probabilities along the gradient are represented as local
Using generative adversarial networks to improve deep-learning fault interpretation networks Deep learning is arguably one of the most important innovations in artificial intelligence in recent times. It allows for computational solutions to proble... Ping,Lu,Matt,... - 《Leading Edge》 被引量: 4发...
et al. CResU-Net: a method for landslide mapping using deep learning. Machine Learning: Science and Technology, 2024, 5(3): 035008. DOI:10.1088/2632-2153/ad5f17 22. Hu, Q., Zhang, Q., Liu, W. et al. Mitigation of urban road collapses based on machine learning via integrating ...
A spectral-temporal constrained deep learning method for tree species mapping of plantation forests using time series Sentinel-2 imagery 2023, ISPRS Journal of Photogrammetry and Remote Sensing Citation Excerpt : China, in particular, owns the largest share of global plantation forests (about 69 millio...
Improving soil organic carbon mapping in farmlands using machine learning models and complex cropping system information Your privacy, your choice We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and ...
This study aims to delineate landslide susceptibility maps using the Analytical Hierarchy Process (AHP) method for the Great Xi’an Region, China, which is a key planning project for urban construction in Shaanxi Province, China from 2021 to 2035. Multip
This paper introduces an intelligent framework for predicting the advancing speed during earth pressure balance (EPB) shield tunnelling. Five artificial intelligence (AI) models based on machine and deep learning techniques—back-propagation neural network (BPNN), extreme learning machine (ELM), support...
1). Then, for the training data, we further split it into 80 % and 20 % for training and validation for the deep learning model's parameterization. We also aggregated the testing data by wards, which are the local government entities in Nepal, and Kincey et al.'s dataset includes 131...
Recent advances in deep learning have been providing non-intuitive solutions to various inverse problems in optics. At the intersection of machine learning and optics, diffractive networks merge wave-optics with deep learning to design task-specific elem