A systematic review of the use of Deep Learning in Satellite Imagery for Agriculture
Agricultural research is essential for increasing food production to meet the needs of a
rapidly growing human population. Collecting large quantities of agricultural data helps to …
rapidly growing human population. Collecting large quantities of agricultural data helps to …
[HTML][HTML] Spatially autocorrelated training and validation samples inflate performance assessment of convolutional neural networks
Deep learning and particularly Convolutional Neural Networks (CNN) in concert with remote
sensing are becoming standard analytical tools in the geosciences. A series of studies has …
sensing are becoming standard analytical tools in the geosciences. A series of studies has …
[HTML][HTML] Deep learning-based individual tree crown delineation in mangrove forests using very-high-resolution satellite imagery
Mangrove forests are vulnerable ecosystems that require broad-scale monitoring. Various
solutions based on satellite imagery have emerged for this purpose but still suffer from the …
solutions based on satellite imagery have emerged for this purpose but still suffer from the …
Early detection of red palm weevil infestations using deep learning classification of acoustic signals
Abstract The Red Palm Weevil (RPW), also known as the palm weevil, is considered among
the world's most damaging insect pests of palms. Current detection techniques include the …
the world's most damaging insect pests of palms. Current detection techniques include the …
KOH activated carbons from Brazil nut shell: Preparation, characterization, and their application in phenol adsorption
Activated carbons named AC105 and AC11 were prepared from Brazil nut shells using the
weight ratios of Brazil nut shells: KOH of 1: 0.5 and 1: 1, respectively. The prepared materials …
weight ratios of Brazil nut shells: KOH of 1: 0.5 and 1: 1, respectively. The prepared materials …
Large-scale date palm tree segmentation from multiscale uav-based and aerial images using deep vision transformers
The reliable and efficient large-scale mapping of date palm trees from remotely sensed data
is crucial for developing palm tree inventories, continuous monitoring, vulnerability …
is crucial for developing palm tree inventories, continuous monitoring, vulnerability …
Fusing multi-season UAS images with convolutional neural networks to map tree species in Amazonian forests
HFP Veras, MP Ferreira, EM da Cunha Neto… - Ecological …, 2022 - Elsevier
Remote sensing images obtained by unoccupied aircraft systems (UAS) across different
seasons enabled capturing of species-specific phenological patterns of tropical trees. The …
seasons enabled capturing of species-specific phenological patterns of tropical trees. The …
Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data
This work proposes a multi-task fully convolutional architecture for tree species mapping in
dense forests from sparse and scarce polygon-level annotations using hyperspectral UAV …
dense forests from sparse and scarce polygon-level annotations using hyperspectral UAV …
[HTML][HTML] Status, advancements and prospects of deep learning methods applied in forest studies
Deep learning, which has exhibited considerable potential and effectiveness in forest
resource assessment, is vital for comprehending and managing forest resources and …
resource assessment, is vital for comprehending and managing forest resources and …
Detection and Mapping of Chestnut Using Deep Learning from High-Resolution UAV-Based RGB Imagery
Y Sun, Z Hao, Z Guo, Z Liu, J Huang - Remote Sensing, 2023 - mdpi.com
The semantic segmentation method based on high-resolution RGB images obtained by
unmanned aerial vehicle (UAV) provides a cost-effective way to improve the accuracy of …
unmanned aerial vehicle (UAV) provides a cost-effective way to improve the accuracy of …