Results 161 to 170 of about 1,587,623 (364)

Cryogenic Neuromorphic Synaptic Behavior in 180 nm Silicon Transistors for Emerging Computing Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
This study investigates the neuromorphic plasticity behavior of 180 nm bulk complementary metal oxide semiconductor (CMOS) transistors at cryogenic temperatures. The observed hysteresis data reveal a signature of synaptic behavior in CMOS transistors at 4 K.
Fiheon Imroze   +8 more
wiley   +1 more source

Machine Learning‐Based Standard Compact Model Binning Parameter Extraction Methodology for Integrated Circuit Design of Next‐Generation Semiconductor Devices

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents a neural network‐based methodology for Berkeley Short‐Channel IGFET Model–Common Multi‐Gate parameter extraction of gate‐all‐around field effect transistors, integrating binning adaptive sampling and transformer neural networks to efficiently capture current–voltage and capacitance–voltage characteristics.
Jaeweon Kang   +4 more
wiley   +1 more source

Accessiblity and validity of smart meter data [PDF]

open access: yes, 2014
Bilton, M   +6 more
core   +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

Predicting Postresection Colorectal Liver Metastases Recurrence Using Advanced Graph Neural Networks with Explainability and Causal Inference

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a framework that combines graph neural networks with causal inference to forecast recurrence and uncover the clinical and pathological factors driving it. It further provides interpretability, validates risk factors via counterfactual and interventional analyses, and offers evidence‐based insights for treatment planning ...
Jubair Ahmed   +3 more
wiley   +1 more source

Cross‐Modal Characterization of Thin‐Film MoS2 Using Generative Models

open access: yesAdvanced Intelligent Systems, EarlyView.
Cross‐modal learning is evaluated using atomic force microscopy (AFM), Raman spectroscopy, and photoluminescence spectroscopy (PL) through unsupervised learning, regression, and autoencoder models. Autoencoder models are used to generate spectroscopy data from the microscopy images.
Isaiah A. Moses   +3 more
wiley   +1 more source

RPSLearner: A Novel Approach Based on Random Projection and Deep Stacking Learning for Categorizing Non‐Small Cell Lung Cancer

open access: yesAdvanced Intelligent Systems, EarlyView.
Identifying non‐small cell lung cancer (NSCLC) subtypes is essential for precision cancer treatment. Conventional methods are laborious, or time‐consuming. To address these concerns, RPSLearner is proposed, which combines random projection and stacking ensemble learning for accurate NSCLC subtyping. RPSLearner outperforms state‐of‐the‐art approaches in
Xinchao Wu, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

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