Results 251 to 260 of about 217,698 (308)

Is Computing with Light All You Need? A Perspective on Codesign for Optical Artificial Intelligence and Scientific Computing

open access: yesAdvanced Intelligent Systems, EarlyView.
This perspective article considers what computations optical computing can and should enable. Focusing upon free‐space optical computing, it argues that a codesign approach whereby materials, devices, architectures, and algorithms are simultaneously optimized is needed.
Prasad P. Iyer   +6 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

Microendovascular Neural Recording from Cortical and Deep Vessels with High Precision and Minimal Invasiveness

open access: yesAdvanced Intelligent Systems, EarlyView.
Intravascular electroencephalography (ivEEG) using micro‐intravascular electrodes was developed. Cortical‐vein ivEEG showed a higher signal‐to‐noise ratio and finer spatial resolution of somatosensory evoked potentials (SEPs) than superior sagittal sinus ivEEG, and deep‐vein ivEEG captured clear visual evoked potentials.
Takamitsu Iwata   +15 more
wiley   +1 more source

Gut mucosa-associated microbiota signatures in healthy individuals and patients at different stages of liver disease: a pilot study. [PDF]

open access: yesGut Pathog
Compare D   +14 more
europepmc   +1 more source

Multitarget Recognition of Flower Images Based on Lightweight Deep Neural Network and Transfer Learning

open access: yesAdvanced Intelligent Systems, EarlyView.
This article proposes a lightweight YOLOv4‐based detection model using MobileNetV3 or CSPDarknet53_tiny, achieving 30+ FPS and higher mAP. It also presents a ShuffleNet‐based classification model with transfer learning and GAN‐augmented images, improving generalization and accuracy.
Qingyang Liu, Yanrong Hu, Hongjiu Liu
wiley   +1 more source

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