Results 151 to 160 of about 766 (173)

Deep learning model BiFPN-YOLOv8m for tree counting in mango orchards using satellite remote sensing data​. [PDF]

Sci Rep
Birla L, Bharadwaj A, Jain R, Deb CK, Sehgal VK, Ramasubramanian V.   +5 more
europepmc   +1 more source

Beyond distance: integrating economic burden into large-scale primary healthcare accessibility analysis. [PDF]

Glob Health Res Policy
Zhu B, Chen L, He Y, Zhang N, Xue H, Bhatt S, Ren M, Mao Y.   +7 more
europepmc   +1 more source

State-of-Art in Studying the Public Health Effects of Heat: A Literature Review. [PDF]

Glob Chall
Gianquintieri L, Caiani EG.
europepmc   +1 more source

SpaCE: a spatial counterfactual explainable deep learning model for predicting out-of-hospital cardiac arrest survival outcome. [PDF]

Int J Geogr Inf Sci
Zhang J, Mu L, Zhang D, Chen Z, Rajbhandari-Thapa J, Pagán JA, Li Y, Mai G, Zhou Z.   +8 more
europepmc   +1 more source

Sen2GF3Floods: A Benchmark Multi-Source Flood Dataset with Dual-Temporal and Active Learning Annotation. [PDF]

Sci Data
Chen W, Zhu Y, Han W, Liu D, Mo G, Xing Z.   +5 more
europepmc   +1 more source

Multiple Representations in geospatial databases, the brain's spatial cells, and deep learning algorithms. [PDF]

Cartogr Geogr Inf Sci
Yuan M.
europepmc   +1 more source

Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction. [PDF]

Sci Rep
Singh G, Moncrieff G, Venter Z, Cawse-Nicholson K, Slingsby J, Robinson TB.   +5 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Improving flood-prone areas mapping using geospatial artificial intelligence (GeoAI): A non-parametric algorithm enhanced by math-based metaheuristic algorithms

Journal of Environmental Management
Flooding presents substantial dangers to human lives and infrastructure, underscoring the need to map flood-prone areas to implement effective mitigation measures precisely. Although machine learning algorithms have made great strides, their accuracy in flood susceptibility mapping (FSM) remains limited due to data dependence, interpretability, and ...
Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Farman Ali   +2 more
exaly   +3 more sources

Introduction to Geospatial Artificial Intelligence (GeoAI)

2023
Song Gao, Yingjie Hu, Wenwen Li
exaly   +2 more sources