-
101
Advection-Free Convolutional Neural Network for Convective Rainfall Nowcasting
Published 2023-01-01“…To address this issue, we present a novel model called the Lagrangian convolutional neural network (L-CNN) that separates the growth and decay of rainfall from motion using the advection equation. …”
Get full text
Article -
102
Multimodal depression detection based on an attention graph convolution and transformer
Published 2025-02-01“…Traditional depression detection methods typically rely on single-modal data, but these approaches are limited by individual differences, noise interference, and emotional fluctuations. …”
Get full text
Article -
103
Prediction of crystalline structure evolution during solidification of aluminum at different cooling rates using a hybrid neural network model
Published 2025-03-01“…The model was trained using a dataset generated from 240 molecular dynamics (MD) simulations conducted at 48 different cooling rates, with cooling rates, timesteps, and temperature as inputs. …”
Get full text
Article -
104
-
105
Denoising of electromagnetic data from different geological blocks using a hybrid PSO-GWO algorithm and CNN
Published 2025-04-01Get full text
Article -
106
CNN-Based Detection of Sheath Incorrect Connection in the Cross-Bonded HV Cable Systems Using the Sheath Current Phasor Difference
Published 2025-01-01Subjects: Get full text
Article -
107
Indian Classical Dance Action Identification and Classification with Convolutional Neural Networks
Published 2018-01-01“…The offline data is created with ten different subjects performing 200 familiar dance mudras/poses from different Indian classical dance forms under various background environments. …”
Get full text
Article -
108
Convolutional Neural Network-Based Low Light Image Enhancement Method
Published 2025-04-01Get full text
Article -
109
Multibranch Adaptive Fusion Graph Convolutional Network for Traffic Flow Prediction
Published 2023-01-01“…In this work, we design the multibranch adaptive fusion graph convolutional network (MBAF-GCN) that explicitly exploits the prior spatial-temporal characteristics at different temporal scales, and each branch is responsible for extracting spatial-temporal features at a specific scale. …”
Get full text
Article -
110
Inverse versus convolution treatment planning algorithms for gamma knife radiosurgery
Published 2024-09-01“…There was significant difference between the two algorithm plans for all dosimetric parameters, with the inverse plan providing higher coverage and selectivity than convolution plan, but taking longer time(p<0.05), while plan was inverse plan better than convolution plan in terms of gradient and conformity (p<0.05). …”
Get full text
Article -
111
Convolutional Edge Constraint-Based U-Net for Salient Object Detection
Published 2019-01-01“…The reason is that the hand-crafted features are the main basis for existing traditional methods to predict salient objects, which results in different pixels belonging to the same object often being predicted different saliency scores. …”
Get full text
Article -
112
Load recognition method based on convolutional neural network and attention mechanism
Published 2025-01-01“…Firstly, the power data of eight different household appliances are collected to establish a U-I trajectory curve database. …”
Get full text
Article -
113
Multiscale network alignment model based on convolution of homogeneous multilayer graphs
Published 2024-12-01“…In terms of node characteristics, the K-nearest neighbor algorithm was used to aggregate node neighborhood information to model the deep network structure, so as to enhance the data. In terms of graph convolution, the convolution process was guided by the construction of a homogeneity matrix according to the network homogeneity, and the social networks of different scales were processed based on the network community structure. …”
Get full text
Article -
114
Meta-path convolution based heterogeneous graph neural network algorithm
Published 2024-03-01“…In the multilayer graph convolution calculation, each node is usually represented as a single vector, which makes the high-order graph convolution layer unable to distinguish the information of different relationships and sequences, resulting in the loss of information in the transmission process. …”
Get full text
Article -
115
Using convolutional neural networks for image semantic segmentation and object detection
Published 2024-12-01“…Convolutional neural networks are widely used for feature extraction in the fields of object detection and image segmentation. …”
Get full text
Article -
116
Convolutional Residual-Attention: A Deep Learning Approach for Precipitation Nowcasting
Published 2020-01-01Get full text
Article -
117
Yoga pose recognition using dual structure convolutional neural network
Published 2025-05-01“…With the development of deep learning technologies, automatic recognition of yoga postures has become popular. To recognize five different yoga postures, this article proposed a dual structure convolutional neural network with a feature fusion function, which consists of the convolutional neural network A (CNN A) and convolutional neural network B (CNN B). …”
Get full text
Article -
118
Identification of DNS covert channel based on improved convolutional neural network
Published 2020-01-01“…In order to effectively identify the multiple types of DNS covert channels,the implementation of different sorts of DNS covert channel software was studied,and a detection based on the improved convolutional neural network was proposed.The experimental results,grounded upon the campus network traffic,show that the detection can identify twenty-two kinds of data interaction modes of DNS covert channels and is able to identify the unknown DNS covert channel traffic.The proposed method outperforms the existing methods.…”
Get full text
Article -
119
Detection algorithm of electronic disguised voice based on convolutional neural network
Published 2018-02-01“…An electronic disguised voice detection algorithm based on the statistical features of MFCC and the convolution neural network was proposed.Firstly,the statistical features of MFCC were extracted and reconstructed as the input of convolution neural network.Considering the convolution kernel size,the number of convolution kernels and the pooling size,24 different network structures were evaluated in this work.Finally,the convolution neural network structure which could be effectively used for electronic disguised voice detection was determined.The experimental results show that the proposed algorithm can effectively detect the trace of electronic disguising.Meanwhile,the specific forgery operation of the electronic disguised voice can also be estimated.…”
Get full text
Article -
120
Research on sketch instruction recognition technology ased on convolutional neural network
Published 2025-04-01“…In order to solve the problems of low accuracy of traditional sketch instruction recognition, a sketch instruction recognition technology based on convolutional neural network is proposed. By constructing and optimizing the convolutional neural network model, a large number of sketch instruction samples are used for training, and the accuracy of the validation set is closely monitored throughout the training process, and the learning rate is dynamically adjusted in real time and based on this. …”
Get full text
Article