Methods and datasets on semantic segmentation for Unmanned Aerial Vehicle remote sensing images: A review

J Cheng, C Deng, Y Su, Z An, Q Wang - ISPRS Journal of Photogrammetry …, 2024 - Elsevier
Abstract Unmanned Aerial Vehicle (UAV) has seen a dramatic rise in popularity for remote-
sensing image acquisition and analysis in recent years. It has brought promising results in …

[HTML][HTML] The segment anything model (sam) for remote sensing applications: From zero to one shot

LP Osco, Q Wu, EL De Lemos, WN Gonçalves… - International Journal of …, 2023 - Elsevier
Segmentation is an essential step for remote sensing image processing. This study aims to
advance the application of the Segment Anything Model (SAM), an innovative image …

Lightweight, pre-trained transformers for remote sensing timeseries

G Tseng, R Cartuyvels, I Zvonkov, M Purohit… - ar** burned areas in Brazilian Pantanal and Amazon with PlanetScope imagery
DN Gonçalves, JM Junior, AC Carrilho… - International Journal of …, 2023 - Elsevier
Pantanal is the largest continuous wetland in the world, but its biodiversity is currently
endangered by catastrophic wildfires that occurred in the last three years. The information …

DeepMineLys: Deep mining of phage lysins from human microbiome

Y Fu, S Yu, J Li, Z Lao, X Yang, Z Lin - Cell reports, 2024 - cell.com
Vast shotgun metagenomics data remain an underutilized resource for novel enzymes.
Artificial intelligence (AI) has increasingly been applied to protein mining, but its …

[HTML][HTML] A lightweight and scalable greenhouse map** method based on remote sensing imagery

W Chen, Q Wang, D Wang, Y Xu, Y He, L Yang… - International Journal of …, 2023 - Elsevier
Seeking a low-cost, high-efficiency greenhouse map** technology has immense
significance. While greenhouse extraction methods using deep learning have been …