As modern computing becomes limited by energy consumption, there is growing interest in physical computing paradigms that can operate closer to fundamental thermodynamic limits. Thermodynamic ...
A new upgoing multi-agent architecture enables ADFWI to coordinate forward modeling, inversion, and interpretation in FWI, allowing information to flow from low-level simulation agents up to ...
In deep learning, the standard approach to accommodate changing task demands is to train new output layers on top of a common trunk network, and, if needed, to relearn synapses throughout the whole ...
In today’s data-driven world, enterprises face numerous challenges in extracting insights from data for informed decision making. Traditional approaches often fall short when handling the complexity ...
The architecture of our RDLUF with $K$ stages (iterations). RDLGD and PM denote the Residual Degradation Learning Gradient Descent module and the Proximal Mapping ...
Abstract: In this paper, we study autonomous landing scene recognition with knowledge transfer for drones. Considering the difficulties in aerial remote sensing, especially that some scenes are ...
Every 20 seconds a limb is amputated somewhere in the world due to diabetes. This is a global health problem that requires a global solution. The International Conference on Medical Image Computing ...
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