Prediction of compressive strength of nano-silica concrete by using random forest algorithm
The prediction of compressive strength in concrete is an important part of civil engineering
because it influences structural design and durability. Recent improvements have brought …
because it influences structural design and durability. Recent improvements have brought …
Insect identification in the wild: The ami dataset
Insects represent half of all global biodiversity, yet many of the world's insects are
disappearing, with severe implications for ecosystems and agriculture. Despite this crisis …
disappearing, with severe implications for ecosystems and agriculture. Despite this crisis …
FoMo-Bench: a multi-modal, multi-scale and multi-task Forest Monitoring Benchmark for remote sensing foundation models
Forests are an essential part of Earth's ecosystems and natural systems, as well as providing
services on which humanity depends, yet they are rapidly changing as a result of land use …
services on which humanity depends, yet they are rapidly changing as a result of land use …
A systematic review on potential analogy of phytobiomass and soil carbon evaluation methods: Ethiopia insights
Y Gelaye - Open Agriculture, 2024 - degruyter.com
Forests play a crucial role in mitigating the impacts of climate change by sequestering
carbon in their biomass and soil. However, Ethiopia faces the threat of soil carbon emissions …
carbon in their biomass and soil. However, Ethiopia faces the threat of soil carbon emissions …
[PDF][PDF] ADistribution SHIFT BENCHMARK FOR SMALL-HOLDER AGROFORESTRY: DO FOUNDATION MODELS IMPROVE GEOGRAPHIC GENERALIZATION?
S Sachdeva, I Lopez, C Biradar… - The Twelfth International …, 2024 - ml-for-rs.github.io
Recent improvements in deep learning for remote sensing have shown that it is possible to
detect individual trees using high resolution satellite remote sensing data. However, there …
detect individual trees using high resolution satellite remote sensing data. However, there …
Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas
While advances in machine learning with satellite imagery (SatML) are facilitating
environmental monitoring at a global scale, developing SatML models that are accurate and …
environmental monitoring at a global scale, developing SatML models that are accurate and …
PureForest: A Large-scale Aerial Lidar and Aerial Imagery Dataset for Tree Species Classification in Monospecific Forests
C Gaydon, F Roche - arXiv preprint arXiv:2404.12064, 2024 - arxiv.org
Knowledge of tree species distribution is fundamental to managing forests. New deep
learning approaches promise significant accuracy gains for forest mapping, and are …
learning approaches promise significant accuracy gains for forest mapping, and are …
[PDF][PDF] Forecasting of Crushing Strength of Sustainable Concrete by Employing Deep and Random Forest Machine Learning
PK Tiwari, M Verma - 2024 - researchgate.net
Sustainable concrete is one of the milestone of the concrete industry. This concrete fulfills
the requirements of concrete manufacturing industry such as strengthen, Durability …
the requirements of concrete manufacturing industry such as strengthen, Durability …
[PDF][PDF] Leveraging Prompt-Based Segmentation Models and Large Dataset to Improve Detection of Trees
V Grondin, P Massicotte, M Gaha… - Proceedings of the …, 2024 - assets.pubpub.org
The abundance of unlabeled forest images on the web is a powerful yet untapped resource
to train forestry vision models. Two key challenges limiting the use of these unlabeled …
to train forestry vision models. Two key challenges limiting the use of these unlabeled …
Insect Identification in the Wild: The AMI Dataset
JS Canas, L Pasi, N Pinoy, F Helsing, JA Russo… - Springer
Insects represent half of all global biodiversity, yet many of the world's insects are
disappearing, with severe implications for ecosystems and agriculture. Despite this crisis …
disappearing, with severe implications for ecosystems and agriculture. Despite this crisis …