Results 221 to 230 of about 680,508 (291)

Spikoder: Dual‐Mode Graphene Neuron Circuit for Hardware Intelligence

open access: yesAdvanced Intelligent Systems, EarlyView.
Spikoder, a graphene leaky integrate‐and‐fire circuit that operates as an encoder and a neuron in a spiking neural network (SNN), is introduced. A Spikoder‐driven double‐layer SNN shows an accuracy of 97.37% for the classification of the Modified National Institute of Standards and Technology dataset, demonstrating its potential as a key building block
Kannan Udaya Mohanan   +4 more
wiley   +1 more source

Discrete Mathematical Structures in Computer Science

open access: green, 2015
D.N. Georgiou   +2 more
openalex   +1 more source

A Data‐Centric Approach to Quantifying the Forward and Inverse Relationship Between Laser Powder Bed Fusion Process Parameters and as‐Built Surface Roughness of IN718 Parts

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces the first inverse machine learning model to predict laser powder bed fusion process parameters for targeted surface roughness of Inconel 718 parts. Unlike prior approaches, it incorporates spatial surface characteristics for improved accuracy.
Samsul Mahmood, Bart Raeymaekers
wiley   +1 more source

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck   +4 more
wiley   +1 more source

Bidirectional multi-nodes quantum teleportation using discrete-time quantum walk. [PDF]

open access: yesSci Rep
Ikken N   +6 more
europepmc   +1 more source

Elastic Fast Marching Learning from Demonstration

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents Elastic Fast Marching Learning (EFML), a novel approach for learning from demonstration that combines velocity‐based planning with elastic optimization. EFML enables smooth, precise, and adaptable robot trajectories in both position and orientation spaces.
Adrian Prados   +3 more
wiley   +1 more source

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