oxidant
发表于 2025-3-26 21:45:40
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dialect
发表于 2025-3-27 02:37:12
Towards Grasping with Spiking Neural Networks for Anthropomorphic Robot Handsdify them during execution based on the shape and the intended interaction with objects. We present a hierarchical spiking neural network with a biologically inspired architecture for representing different grasp motions. We demonstrate the ability of our network to learn from human demonstration us
HAUNT
发表于 2025-3-27 09:11:01
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peritonitis
发表于 2025-3-27 13:16:37
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暴发户
发表于 2025-3-27 15:27:34
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QUAIL
发表于 2025-3-27 20:40:11
Sensorimotor Prediction with Neural Networks on Continuous Spacestelligence argue that sensorimotor prediction is a fundamental building block of cognition. In this paper, we learn the sensorimotor prediction on data captured by a mobile robot equipped with distance sensors. We show that Neural Networks can learn the sensorimotor regularities and perform sensorim
Enervate
发表于 2025-3-28 01:12:13
Classifying Bio-Inspired Model of Point-Light Human Motion Using Echo State Networksan action descriptor. The Echo State Network (ESN) which also has a biological plausibility is chosen for classification. We demonstrate the efficiency and robustness of applying the proposed feature extraction technique with ESN by constraining the test data based on arbitrary untrained viewpoints,
碎石
发表于 2025-3-28 03:00:18
A Prediction and Learning Based Approach to Network Selection in Dynamic Environmentsemented in static network environments while cannot handle unpredictable dynamics in practice. In this paper, we propose a prediction and learning based approach, which considers both the fluctuation of radio resource and the variation of user demand. The network selection scenario is modeled as a m
不幸的人
发表于 2025-3-28 06:29:15
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抛射物
发表于 2025-3-28 11:22:06
Learning Distance-Behavioural Preferences Using a Single Sensor in a Spiking Neural Networkle non-calibrated sensor in combination with neural elements could provide flexibility through learning, to effectively cope with changing environments. The objective of this study was to design an adaptive system with the potential capability of learning behavioural preferences in relation to disti