MVHGCN: Predicting circRNA-disease associations with multi-view heterogeneous graph convolutional neural networks. by Yan Miao, Xuan Tang, Chunyu Wang, Zhenyuan Sun, Guohua Wang, Shan Huang

“…MVHGCN first constructs a heterogeneous graph and generates feature descriptors by integrating multiple databases. Then it extracts different connection views of circRNA and diseases through meta-paths, maximizing the utilization of known association information, and aggregates deep feature information through graph convolutional networks. …”
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Algorithm development for recognizing human emotions using a convolutional neural network based on audio data by V. V. Semenuk, M. V. Skladchikov

“…To validate the neural network different set of audio data, not participating in the training, was selected. …”
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Bearing fault diagnosis for variable operating conditions based on KAN convolution and dual branch fusion attention by Qibing Wang, Chuanjie Yin, Kun She, Qinfeng Tong, Guoxiong Lu, Hongbing Zhang, Jiawei Lu

“…Firstly, a new structure of KANs is applied to Convolutional Neural Networks (CNN) for replacing traditional linear convolutional kernels. …”
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Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferences by Xishi Liu, Haolin Wang, Dan Li

“…In our research, we propose a novel suggestion model of short video material for international video apps through user preference modelling via hybrid multi-modal GCN (graph convolutional network). Unlike traditional methods that rely on the overall metadata of the short movies only, our approach jointly considers visual, linguistic and audio features of short movies, as well as user interactions, to propose personalized recommendations. …”
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Bidirectional convolutional recurrent neural network architecture with group-wise enhancement mechanism for text sentiment classification by Aytuğ Onan

“…In addition, such models value different features equally. To solve these issues, we propose a bidirectional convolutional recurrent neural network architecture, which utilizes two separate bidirectional LSTM and GRU layers, to derive both past and future contexts by connecting two hidden layers of opposite directions to the same context. …”
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Robust Classification of Encrypted Network Services Using Convolutional Neural Networks Optimized by Information Bottleneck Method by Zhijiong Wang, Wei Lin, Yu Chen, Mang I. Vai

“…This paper proposes a novel approach to achieve robust classification of encrypted network services using Convolutional Neural Networks (CNNs) optimized by the Information Bottleneck (IB) method (IB-CNN). …”
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RETRACTED ARTICLE: Detection of hate: speech tweets based convolutional neural network and machine learning algorithms by Hameda A. Sennary, Ghada Abozaid, Ashraf Hemeida, Alexey Mikhaylov

“…The classifiers involved are Logistic Regression (LR), Naive Bayes (NB), Multi-layer Perceptron (MLP), and Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbor (KNN), K-Means, Decision Tree (DT), Gradient Boosting classifier (GBC), and the Extra Trees (ET) in addition to the convolutional neural network (CNN). Maximum accuracy was attained, which exceeded 99%.…”
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Convolutional neural network (CNN) based month’s name recognition in Gurumukhi script for Punjab state of India by Tajinder Pal Singh, Sheifali Gupta, Jamil Hussain, Sapna Juneja, Meenu Garg, Deepali Gupta, Majed Alsafyani

“…For this work, a dataset of 24,000 word images of 24 different Gurumukhi months has also been prepared from 500 distinct writers. …”
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MCTGNet: A Multi-Scale Convolution and Hybrid Attention Network for Robust Motor Imagery EEG Decoding by Huangtao Zhan, Xinhui Li, Xun Song, Zhao Lv, Ping Li

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Enhancing Recognition and Categorization of Skin Lesions with Tailored Deep Convolutional Networks and Robust Data Augmentation Techniques by Syed Ibrar Hussain, Elena Toscano

“…This study introduces deep convolutional neural network-based methods for the detection and classification of skin lesions, enhancing system accuracy through a combination of architectures, pre-processing techniques and data augmentation. …”
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Sparse convolutional neural network acceleration with lossless input feature map compression for resource‐constrained systems by Jisu Kwon, Joonho Kong, Arslan Munir

“…With several design optimization techniques, the authors have implemented their technique in a field‐programmable gate array (FPGA) system‐on‐chip platform and evaluated their technique for six different convolutional layers in SqueezeNet. Results reveal that the authors' technique improves the performance by 1.1×–22.6× while reducing energy consumption by 47.7%–97.4% as compared to the CPU‐based execution. …”
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Data-Driven Prediction of Grape Leaf Chlorophyll Content Using Hyperspectral Imaging and Convolutional Neural Networks by Minglu Zeng, Xinghui Zhu, Ling Wan, Jian Xu, Luming Shen

“…Subsequently, the study discussed 15 different spectral preprocessing methods, selecting fast Fourier transform (FFT) as the optimal approach. …”
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A road generalization method using graph convolutional network based on mesh-line structure unit by Tianyuan Xiao, Tinghua Ai, Dirk Burghardt, Pengcheng Liu, Min Yang, Aji Gao, Bo Kong, Huafei Yu

“…On the other hand, existing methods tend to consider individual structures separately in different algorithms, such as strokes, meshes and graph networks, lacking a solution that brings the advantages of these methods together. …”
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Convolutional neural network for the early identification of weeds: A technological support to biodiversity and yield losses mitigation by Claudio Russo, Valerio Cirillo, Marco Esposito, Matteo Lentini, Nausicaa Pollaro, Albino Maggio

“…With this study, we assessed the possibility of applying two convolutional neural networks (CNN) for the recognition of different classes of weeds in a winter wheat (T. aestivum) cultivation based on RGB images. …”
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A Spatiotemporal Convolutional Neural Network Model Based on Dual Attention Mechanism for Passenger Flow Prediction by Jinlong Li, Haoran Chen, Qiuzi Lu, Xi Wang, Haifeng Song, Lunming Qin

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Spatio-temporal Graph Convolutional Neural Network for traffic signal prediction in large-scale urban networks by Shimon Komarovsky, Jack Haddad

“…Different dataset and features are considered. In the first model, prediction of speed data is examined, while in the second model green times and speed are predicted. …”
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Research on Urban Road Traffic Flow Prediction Based on Sa-Dynamic Graph Convolutional Neural Network by Song Hu, Jian Gu, Shun Li

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A Novel Dilated Convolution Light Weight Neural Network (DCLW-NN) for the Classification of Breast Thermograms by S. Malathi, A. Shenbagavalli, N. Sriraam

“…In this paper, we have presented a novel Dilated Convolution Light Weight Neural Network (DCLW-NN) to analyze the breast thermograms. …”
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LS-MambaNet: Integrating Large Strip Convolution and Mamba Network for Remote Sensing Object Detection by Lingyu Yan, Zijian He, Zhiqi Zhang, Guangqi Xie

“…Specifically, firstly, a group fusion strategy is combined with the introduction of large-band convolution to adaptively adjust the receptive domains of the features, which enhances the spatial context information extraction for objects with high aspect ratios. …”
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Identification of Fake Comments in E-Commerce Based on Triplet Convolutional Twin Network and CatBoost Model by Juanjuan Peng

“…To promote the development of e-commerce, a false comment recognition model based on triplet convolutional twin network and CatBoost model is proposed. …”
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