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Multiple Unmanned Aerial Vehicle Formation Control through Deep Reinforcement Learning with Offline Sample Correction

open access: yesAdvanced Intelligent Systems, EarlyView.
Herein, a deep reinforcement learning‐based multi‐UAV formation control approach is proposed. By optimizing the utilization of historical data through correcting of offline samples, the past experience is better leveraged and learning performance is improved.
Zhongkai Chen   +4 more
wiley   +1 more source

Improving Long‐Term Glucose Prediction Accuracy with Uncertainty‐Estimated ProbSparse‐Transformer

open access: yesAdvanced Intelligent Systems, EarlyView.
Wearable devices collect blood glucose and other physiological data, which serve as inputs to the prediction model. After data embedding, a structure utilizing ProbSparse self‐attention and a one‐step generative head within a Transformer‐based model is introduced, which is concurrently designed for deployment on edge devices, enabling real‐time ...
Wei Huang   +5 more
wiley   +1 more source

An Ultrathin and Lightweight Soft Inflatable Actuator for Natural Tactile Sensory Feedback

open access: yesAdvanced Intelligent Systems, EarlyView.
A lightweight, ultrathin soft actuator mimics natural touch by delivering strong, multimodal haptic feedback through pressure and vibration. Tested on both able‐bodied individuals and amputees, it achieves high sensory precision in a compact form. Its simplicity, power, and adaptability hint at transformative applications in prosthetics, immersive ...
Hanna Scherer   +7 more
wiley   +1 more source

Memimpedance‐Based Biomolecular Device for Adaptive Physical Reservoir Computing

open access: yesAdvanced Intelligent Systems, EarlyView.
By integrating fast‐switching ion‐channel‐based memristive and slow‐switching biomembrane‐based memcapacitive nodes within droplet interface bilayers, this hybrid memimpedance reservoir overcomes the memory‐nonlinearity trade‐off and extends temporal adaptability.
Ahmed S. Mohamed   +3 more
wiley   +1 more source

BiT‐HyMLPKANClassifier: A Hybrid Deep Learning Framework for Human Peripheral Blood Cell Classification Using Big Transfer Models and Kolmogorov–Arnold Networks

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents BiT‐HyMLPKANClassifier, a novel hybrid deep learning framework for automated human peripheral blood cell classification. Model combines Big Transfer models with multilayer perceptron and efficient Kolmogorov–Arnold Network architectures, achieving over 97% accuracy.
Ömer Miraç KÖKÇAM, Ferhat UÇAR
wiley   +1 more source

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