The widespread use of black-box AI models has raised the need for algorithms and methods that explain the decisions made by these models.
The results demonstrate that ITX outperforms all baseline methods by at least 5% (equivalent to $70, 000 for a 6, 000 vehicle operation) per week in terms of a monetary reward function which was modeled to replicate the profitability of a real-world ridepooling system.
Despite the plethora of successful Super-Resolution Reconstruction (SRR) models applied to natural images, their application to remote sensing imagery tends to produce poor results.
Estimating the heightmaps of buildings and vegetation in single remotely sensed images is a challenging problem.
Over the past couple of decades, the number of wildfires and area of land burned around the world has been steadily increasing, partly due to climatic changes and global warming.
A challenge of the computer vision community is to understand the semantics of an image, in order to allow image reconstruction based on existing high-level features or to better analyze (semi-)labelled datasets.
In this paper, a simulation is performed using the area of Catalonia, Spain as a case study for the characteristic low SOC in the Mediterranean, to examine whether animal manure can improve substantially the SOC of agricultural fields, when applied as organic fertilizers.
Natural forests are complex ecosystems whose tree species distribution and their ecosystem functions are still not well understood.
Intensive livestock production might have a negative environmental impact, by producing large amounts of animal manure, which, if not properly managed, can contaminate nearby water bodies with nutrient excess.
Intensive livestock production might have a negative environmental impact, by producing large amounts of animal excrements, which, if not properly managed, can contaminate nearby water bodies with nutrient excess.
Eighteen samples made by different milk mixtures and produced in different areas of the country were analyzed, to reveal that Halloumi microbiome was mainly comprised by lactic acid bacteria (LAB), including Lactobacillus, Leuconostoc, and Pediococcus, as well as halophilic bacteria, such as Marinilactibacillus and Halomonas.
However, the performance of predicting in- and outflux is less sensitive to the prediction horizon.
This paper describes preliminary work in the recent promising approach of generating synthetic training data for facilitating the learning procedure of deep learning (DL) models, with a focus on aerial photos produced by unmanned aerial vehicles (UAV).
Natural computing offers new opportunities to understand, model and analyze the complexity of the physical and human-created environment.
Monitoring of disasters is crucial for mitigating their effects on the environment and human population, and can be facilitated by the use of unmanned aerial vehicles (UAV), equipped with camera sensors that produce aerial photos of the areas of interest.