Results 251 to 260 of about 129,870 (304)
The digitization of RBetno (JBRJ) represents a step forward for biodiversity conservation in Brazil. Aligned with the Kunming‐Montreal Global Biodiversity Framework (Target 2, 2020–2030), this project documents the use of plants, including traditional knowledge and vernacular names, with a focus on the Atlantic Forest and Amazon.
Viviane S. Fonseca‐Kruel +6 more
wiley +1 more source
IVA-FL: An information-value-aware federated learning framework for Privacy-Preserving Financial data Risk Management. [PDF]
Wu J +5 more
europepmc +1 more source
Federated Learning of Neural ODE Models with Different Iteration Counts
Yuto Hoshino +2 more
openalex +2 more sources
This study develops a method to identify the source areas of precipitation events, as illustrated for the western part of the Netherlands. Radar‐based precipitation data are traced back to their source areas and machine‐learning techniques are used to identify hypothesized causes: urban heat, surface roughness, and air pollution. We find that urban and
Jelmer van der Graaff +1 more
wiley +1 more source
Federated Learning Architecture for 3D Breast Cancer Image Classification. [PDF]
Ali Alhussan A +4 more
europepmc +1 more source
Federated Autonomous Deep Learning for Distributed Healthcare System
Rakesh Mohan Pujahari +2 more
openalex +1 more source
ABSTRACT Accurate state of health (SOH) estimation of Li‐ion batteries is essential for ensuring safety, reliability, and prolonging battery lifespan in energy storage systems and electric vehicles. This study proposes a hybrid temporal convolutional network (TCN)–transformer framework that effectively captures both short‐term temporal dynamics and ...
Fusen Guo +6 more
wiley +1 more source
Federated Learning in Healthcare Ethics: A Systematic Review of Privacy-Preserving and Equitable Medical AI. [PDF]
Mir BA, Abbas SR, Lee SW.
europepmc +1 more source
Survey on AI‐Enabled Computer Vision Technologies and Applications for Space Robotic Missions
ABSTRACT This survey provides a comprehensive overview of recent advancements and challenges in Artificial Intelligence (AI)‐enabled computer vision (CV) techniques for space robotic missions, spanning critical phases such as Entry, Descent, and Landing (EDL), orbital operations, and planetary surface exploration.
Maciej Quoos +6 more
wiley +1 more source

