Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies
… of inclusion/exclusion predictions obtained from our model via … trend cited in impact studies
matches, in sign, magnitude or … no substitute for careful assessment by experts, either in the …
matches, in sign, magnitude or … no substitute for careful assessment by experts, either in the …
[HTML][HTML] A machine learning-based approach for wildfire susceptibility mapping. The case study of the Liguria region in Italy
M Tonini, M D'Andrea, G Biondi, S Degli Esposti… - Geosciences, 2020 - mdpi.com
… on statistical models, often improved by expert knowledge for … map the spatial distribution
of a burned area and to predict … ie, spatially aligned) to match the same reference image with …
of a burned area and to predict … ie, spatially aligned) to match the same reference image with …
[HTML][HTML] Combining expert and crowd-sourced training data to map urban form and functions for the continental US
… provides a CONUS-wide LCZ classification for 2017 and is provided on a 100 m spatial
resolution in the Albers Conic Equal Area projection (matching the projection of the NLCD maps …
resolution in the Albers Conic Equal Area projection (matching the projection of the NLCD maps …
Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs
… matching of species’ trait values to environmental conditions. Models that use traits to predict
the success of a species … and other, as assigned based on expert opinion (available in the …
the success of a species … and other, as assigned based on expert opinion (available in the …
[HTML][HTML] Mapping crop types in southeast India with smartphone crowdsourcing and deep learning
… In the sensitivity analyses, we compared the performance of models trained on expert-… The
predicted crop type map matches broad patterns of Plantix submission data and government …
predicted crop type map matches broad patterns of Plantix submission data and government …
Learning with limited annotations: a survey on deep semi-supervised learning for medical image segmentation
… imaging domain where only experts can provide reliable and … network to predict the loss
map of the teacher’s prediction. … image with predicted segmentation probability maps instead …
map of the teacher’s prediction. … image with predicted segmentation probability maps instead …
Range edges in heterogeneous landscapes: Integrating geographic scale and climate complexity into range dynamics
… use data on species distributions in contrasting landscapes to … tree species (Little/USGS
expert range maps). Hemispheric … The colors of the points match the histogram, indicating how …
expert range maps). Hemispheric … The colors of the points match the histogram, indicating how …
De novo protein design by deep network hallucination
… , and these closely matched the hallucinated models. Thus, … the network-predicted distance
and orientation maps were as … to those encoded by expert protein designers using more …
and orientation maps were as … to those encoded by expert protein designers using more …
Machine intelligence for chemical reaction space
… from atom-mapping, but also that the model predictions provide chemists with more … NameRXN
categorizes reactions into more than 1800 classes if the reactions match expert templates…
categorizes reactions into more than 1800 classes if the reactions match expert templates…
[HTML][HTML] Optimized deep learning model as a basis for fast UAV mapping of weed species in winter wheat crops
… Experts examined all UAV images and … of MATCH, the correct predictions of the category
MATCH are called TP. FP summarizes cases in which MATCH is falsely predicted as MATCH …
MATCH are called TP. FP summarizes cases in which MATCH is falsely predicted as MATCH …