Sines, transient, noise neural modeling of piano notes by Riccardo Simionato, Stefano Fasciani

“…The noise sub-module uses a learnable time-varying filter, and the transients are generated using a deep convolutional network. From singular notes, we emulate the coupling between different keys in trichords with a convolutional-based network. …”
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Application research of 3D virtual interactive technology in interactive teaching of arts and crafts by Mingqi Yao

“…For this reason, the research proposes an image denoising model based on convolutional neural network and wavelet transform, which adopts residual neural network structure and batch normalization algorithm, aiming at gradient explosion and gradient disappearance that may be caused by convolutional neural network, And the problem of low training efficiency has been optimized. …”
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Automatic pine wilt disease detection based on improved YOLOv8 UAV multispectral imagery by Shaoxiong Xu, Wenjiang Huang, Dacheng Wang, Biyao Zhang, Hong Sun, Jiayu Yan, Jianli Ding, Jinjie Wang, Qiuli Yang, Tiecheng Huang, Xu Ma, Longlong Zhao, Zhuoqun Du

“…In this study, UAV multispectral imagery was used to analyze the sensitive spectral bands and different vegetation indices for PWD discriminability. …”
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Fast panoramic image stitching algorithm based on parameter regression by Fan GUO, Xiaohu LI, Wentao LIU, Jin TANG

“…In reality, the field of view of images acquired by cameras was usually limited, and the demand for panoramic images was increasing.Therefore, a fast panoramic image stitching algorithm based on parameter regression was proposed for panoramic image sequences.The traditional image registration task was transformed into deep learning combined with machine learning, a multi-scale deep convolutional neural network (MDCNN) based on Gaussian difference pyramid was designed to extract features of stitching images, and LightGBM regression model was used to predict stitching parameters.The transformation matrix and the focal length of the camera were obtained to align the images, and a hyperbolic image fusion algorithm was designed to eliminate the stitching seam between the images.The experimental results show that the proposed algorithm can quickly mosaic images and obtain clearer and more natural panoramic mosaic effects than the existing representative algorithms.It also has good adaptability for infrared images.…”
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BeatProfiler: Multimodal In Vitro Analysis of Cardiac Function Enables Machine Learning Classification of Diseases and Drugs by Youngbin Kim, Kunlun Wang, Roberta I. Lock, Trevor R. Nash, Sharon Fleischer, Bryan Z. Wang, Barry M. Fine, Gordana Vunjak-Novakovic

“…We further apply Grad-CAM on our convolution-based models to identify signature regions of perturbations by these drugs in calcium signals. …”
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Directional properties of the loudspeaker systems with analog and digital crossover networks by Marek NIEWIAROWICZ, Henryk ŁOPACZ

“…The set of impulse responses for different angles in the whole sphere around the loudspeaker system were measured and then, applying a convolution with the excitation signals of the "tone burst" type, for some specific frequencies from the cut-off region of crossover networks, the directional characteristics have been calculated for the steady and transient states. …”
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Single-Pixel Imaging Based on Enhanced Multi-Network Prior by Jia Feng, Qianxi Li, Jiawei Dong, Qing Zhao, Hao Wang

“…The SAE makes use of the measurement dimension information and uses the group inverse to obtain the decoding matrix to enhance its generalization. The Unet uses different size convolution kernels and attention mechanisms to enhance feature extraction capabilities. …”
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ResnetCPS for Power Equipment and Defect Detection by Xingyu Yan, Lixin Jia, Xiao Liao, Wei Cui, Shuangsi Xue, Dapeng Yan, Hui Cao

“…The core idea is that the network output should remain consistent for the same object at different scales. The proposed framework facilitates weight sharing across different layers within the convolutional network, establishing connections between pertinent channels across layers and leveraging the scale invariance inherent in image datasets. …”
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The analysis of motion recognition model for badminton player movements using machine learning by Xuanmin Zhu, Lizhi Liu, Jingshuo Huang, Genyan Chen, Xi Ling, Yanshuo Chen

“…A badminton stroke recognition method based on Quantum Convolutional Neural Network (QCNN) is proposed. It is then compared with traditional Support Vector Machines (SVM) and Convolutional Neural Network (CNN). …”
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Electrowetting display of multiscale Gamma based on dynamic histogram equilibrium by Mingzhen Chen, Zhixian Lin, Shanling Lin, Jianpu Lin, Tailiang Guo

“…Then, corresponding compensation weights are designed based on the different reflection brightness. Furthermore, the illumination component is extracted by multi-scale Gaussian convolution, and multi-scale gamma correction based on different photoelectric characteristics is designed. …”
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Liver segmentation network based on detail enhancement and multi-scale feature fusion by Lu Tinglan, Qin Jun, Qin Guihe, Shi Weili, Zhang Wentao

“…Additionally, 2D CT images obtained from different angles (such as sagittal, coronal, and transverse planes) increase the diversity of liver morphology and the complexity of segmentation. …”
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Driving by a Publicly Available RGB Image Dataset for Rice Planthopper Detection and Counting by Fusing Swin Transformer and YOLOv8-p2 Architectures in Field Landscapes by Xusheng Ji, Jiaxin Li, Xiaoxu Cai, Xinhai Ye, Mostafa Gouda, Yong He, Gongyin Ye, Xiaoli Li

“…Additionally, the Spatial and Channel Reconstruction Convolution (SCConv) was applied, replacing Convolution (Conv) in the C2f module of YOLOv8. …”
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Enhanced prediction of hemolytic activity in antimicrobial peptides using deep learning-based sequence analysis by Ibrahim Abdelbaky, Mohamed Elhakeem, Hilal Tayara, Elsayed Badr, Mustafa Abdul Salam

“…Peptide sequences are represented using one-hot encoding, and the CNN architecture consists of multiple convolutional and fully connected layers. The model was trained on six different datasets: HemoPI-1, HemoPI-2, HemoPI-3, RNN-Hem, Hlppredfuse, and AMP-Combined, achieving Matthew’s correlation coefficients of 0.9274, 0.5614, 0.6051, 0.6142, 0.8799, and 0.7484, respectively. …”
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Multibranch 3D-Dense Attention Network for Hyperspectral Image Classification by Junru Yin, Changsheng Qi, Wei Huang, Qiqiang Chen, Jiantao Qu

“…This network is able to reuse features to fully exploit the shallow spatial-spectral information of HSI. Meanwhile, the convolutional kernels of different sizes are used to extract multi-scale spatial-spectral features. …”
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Red Tide Detection Method Based on a Time Series Fusion Network Model: A Case Study of GOCI Data in the East China Sea by Tianhong Ding, Zhiqiang Xu, Yunjie Wang, Qinglian Hou, Xiangyong Liu, Fengshuang Ma

“…Additionally, an ECA channel attention mechanism is employed to fully exploit spectral features across different bands for deeper feature extraction. A novel feature extraction module, ASPC-DSC, combines atrous spatial pyramid convolution with depthwise separable convolution to effectively fuse multi-scale contextual features while improving computational efficiency. …”
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Building Footprint Extraction from High Resolution Aerial Images Using Generative Adversarial Network (GAN) Architecture by Arnick Abdollahi, Biswajeet Pradhan, Shilpa Gite, Abdullah Alamri

“…Thus, we introduce an end-to-end convolutional neural network called Generative Adversarial Network (GAN) in this study to tackle these issues. …”
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Health Monitoring of Carbon Fiber Reinforced Building Materials Based on Phase Unwrapping Algorithm by Min Yan, Jianjun Zhou, Shuai Guo, Yanlong Li

“…Therefore, a hybrid model to monitor carbon fiber reinforced building materials based on the least squares phase unwrapping and deep convolutional neural networks is developed to provide timely warning of damage factors. …”
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Comparison of neural networks for suppression of multiplicative noise in images by V.A. Pavlov, A.A. Belov, V.T. Nguen, N. Jovanovski, A.S. Ovsyannikova

“…It is shown that different architectures require significantly different amount of training data to reach the same noise suppression quality. …”
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HyperspectralMamba: A Novel State Space Model Architecture for Hyperspectral Image Classification by Jianshang Liao, Liguo Wang

“…The method addresses limitations in existing techniques through three key innovations: (1) a novel dual-stream architecture that combines SSM global modeling with parallel convolutional local feature extraction, distinguishing our approach from existing single-stream SSM methods; (2) a band-adaptive feature recalibration mechanism specifically designed for hyperspectral data that adaptively adjusts the importance of different spectral band features; and (3) an effective feature fusion strategy that integrates global and local features through residual connections. …”
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Fault Diagnosis for Bearing Based on 1DCNN and LSTM by Haibin Sun, Shichao Zhao

“…In this paper, an end-to-end intelligent fault diagnosis method for bearing combining one-dimensional convolutional neural network with long short-term memory network (1DCNN-LSTM) is proposed for the deficiencies of existing fault diagnosis methods. …”
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