Results 81 to 90 of about 250,191 (314)
IEEE Access, 2020 In this paper, ultrasound imaging of benign and malignant thyroid nodules to predict the depth of the learning algorithm, built on circulation volume product thyroid ultrasound image neural network forecasting model.
Yinghui Lu, Yi Yang, Wan Chen
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Homological Convolutional Neural Networks
CoRR, 2023 Deep learning methods have demonstrated outstanding performances on classification and regression tasks on homogeneous data types (e.g., image, audio, and text data). However, tabular data still pose a challenge, with classic machine learning approaches being often computationally cheaper and equally effective than increasingly complex deep learning ...
Antonio Briola +3 more
openaire +3 more sources
Advanced Engineering Materials, EarlyView.This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Electromagnetic Imaging of Uniaxial Objects by Two-Step Neural Network [PDF]
The integration of electromagnetic imaging technology with the Internet of Things plays an important role in fields as diverse as healthcare, geophysics, and industrial diagnostics.
Chien, Wei;Chiu, Chien-Ching;Chen, Po-Hsiang;Wu, Hung-Yu;Lim, Eng Hock
core +1 more source
Advancements in English listening education: Chat GPT and convolutional neural network integration [PDF]
, 2023 In today's globalized world, strong English listening skills have become more essential than ever before. Whether you're a language learner, a professional conducting business internationally, or a traveler exploring new cultures, the ability to ...
Runmei Xing
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Turkish Journal of Orthodontics, 2022 Objective: The aim of this study is to develop an artificial intelligence model to detect cephalometric landmark automatically enabling the automatic analysis of cephalometric radiographs which have a very important place in dental practice and is used ...
Mehmet Uğurlu
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Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification
IEEE Access, 2021 A novel and efficient end-to-end learning model for automatic modulation classification is proposed for wireless spectrum monitoring applications, which automatically learns from the time domain in-phase and quadrature data without requiring the design ...
Kaisheng Liao +4 more
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A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy
Advanced Engineering Materials, EarlyView.A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle +5 more
wiley +1 more source
Fully Convolutional Neural Network with Relation Aware Context Information for Image Parsing [PDF]
, 2021 Image parsing is among the core tasks in the field of computer vision. The automatic pixel-wise segmentation offers great potential in terms of application adaptability.
Azam, Basim +5 more
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Research onconvolutional neural network for reservoir parameter prediction
Tongxin xuebao, 2016 As the branch of artificial intelligence,artificial neural network solved many difficult practical problems in pattern recognition and classification prediction field successfully.However,they cannot learn the feature from networks.In recent years,deep ...
You-xiang DUAN, Gen-tian LI, Qi-feng SUN
doaj +2 more sources