Results 221 to 230 of about 263,222 (303)

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

open access: yesAdvanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian   +37 more
wiley   +1 more source

Graft union formation involves interactions among bud signals, carbon availability, dormancy release, wound responses and non-self-communication in grapevine. [PDF]

open access: yesPlant J
Loupit G   +11 more
europepmc   +1 more source

Automated Discovery of Multicellular Behavior for Optimized Plant Growth and Climate Resilience

open access: yesAdvanced Intelligent Systems, EarlyView.
An automated robotic system is described for rapid scientific experimentation with multicellular organisms. By enhancing a robotic liquid handler with a custom developed deep learning algorithm and camera module, samples and data are prepared with minimal human intervention.
Mark A. DeAngelis   +2 more
wiley   +1 more source

Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza   +2 more
wiley   +1 more source

Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes

open access: yesAdvanced Intelligent Systems, EarlyView.
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera   +2 more
wiley   +1 more source

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