Raman Spectroscopy and One‐Dimensional Convolutional Neural Networks for the Forensic Identification of Red Stamp Inks in Questioned Documents
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Raman Spectroscopy"
DOI: 10.1002/jrs.70018
Abstract: The accurate classification of ink samples, which are inherently complex mixtures, is critical for verifying the authenticity of historical artworks and financial documents such as contracts, insurance claims, wills, and tax records. Herein, one‐dimensional convolutional… read more here.
Keywords: spectroscopy; convolutional neural; dimensional convolutional; one dimensional ... See more keywords
Design of ultra-wideband antenna based on one-dimensional convolutional neural network
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Microwave and Wireless Technologies"
DOI: 10.1017/s1759078725000303
Abstract: This paper presents a notched ultra-wideband antenna designed to suppress interference from narrowband communication systems. The antenna features a defected ground structure and a stepped microstrip feedline for improved impedance matching and enhanced bandwidth. A… read more here.
Keywords: convolutional neural; ultra wideband; dimensional convolutional; antenna ... See more keywords
Three-Dimensional Convolutional Neural Networks Utilizing Molecular Topological Features for Accurate Atomization Energy Predictions.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.1c00504
Abstract: Deep learning methods provide a novel way to establish a correlation between two quantities. In this context, computer vision techniques such as three-dimensional (3D)-convolutional neural networks become a natural choice to associate a molecular property… read more here.
Keywords: neural networks; molecular topological; convolutional neural; dimensional convolutional ... See more keywords
One-dimensional convolutional neural network-based analysis of dielectric spectral abundance in liquid-phase media
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-86667-8
Abstract: Aiming at the difficult problem of component information analysis of mixed dielectric spectra, the component information characteristics of mixed dielectric spectra are investigated by one-dimensional convolutional neural network, and the component analysis of mixed media… read more here.
Keywords: convolutional neural; dielectric spectra; analysis; dimensional convolutional ... See more keywords
Semisupervised hyperspectral imagery classification based on a three-dimensional convolutional adversarial autoencoder model with low sample requirements
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Applied Remote Sensing"
DOI: 10.1117/1.jrs.14.024522
Abstract: Abstract. Although there are many state-of-the-art methods for hyperspectral classification, data deficiency is a problem that should be addressed before popularizing hyperspectral technology. To solve this problem, it is worth exploring methods based on small… read more here.
Keywords: semisupervised hyperspectral; adversarial autoencoder; dimensional convolutional; three dimensional ... See more keywords
A Novel Bearing Fault Diagnosis Methodology Based on SVD and One-Dimensional Convolutional Neural Network
Sign Up to like & getrecommendations! Published in 2020 at "Shock and Vibration"
DOI: 10.1155/2020/1850286
Abstract: This paper constructs a novel network structure (SVD-1DCNN) based on singular value decomposition (SVD) and one-dimensional convolutional neural network (1DCNN), which takes the original signal as input to realize intelligent diagnosis of bearing faults. The… read more here.
Keywords: methodology; network; diagnosis; svd one ... See more keywords
Multimodal Biomedical Image Segmentation using Multi-Dimensional U-Convolutional Neural Network
Sign Up to like & getrecommendations! Published in 2024 at "BMC Medical Imaging"
DOI: 10.1186/s12880-024-01197-5
Abstract: Deep learning recently achieved advancement in the segmentation of medical images. In this regard, U-Net is the most predominant deep neural network, and its architecture is the most prevalent in the medical imaging society. Experiments… read more here.
Keywords: convolutional neural; segmentation; dimensional convolutional; neural network ... See more keywords
Fault diagnosis and identification of rotating machinery based on one-dimensional convolutional neural network
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Vibroengineering"
DOI: 10.21595/jve.2024.23722
Abstract: The paper focuses on two kinds of rotating machinery, miniature table drilling machine and automobile engine, as the research object. Traditional machine learning has the need for manual feature extraction, and is very dependent on… read more here.
Keywords: convolutional neural; dimensional convolutional; one dimensional; network ... See more keywords
A Cognitive Load Assessment Method for Airtight Cabin Operators Based on a One-Dimensional Convolutional Neural Network
Sign Up to like & getrecommendations! Published in 2025 at "Symmetry"
DOI: 10.3390/sym17060915
Abstract: Airtight cabins with highly complex human–machine systems impose an excessive cognitive load on operators. However, the traditional cognitive load assessment methods often cannot fully extract physiological features such as electroencephalogram and electrocardiogram signals, relying heavily… read more here.
Keywords: cognitive load; convolutional neural; method; load ... See more keywords