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

“…This is achieved by capturing feature differences and utilising non-local(NL) operations, thereby enhancing the feature representation ability under different working conditions. …”
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Overseas short video recommendations: A multimodal graph convolutional network approach incorporating cultural preferences by Xishi Liu, Haolin Wang, Dan Li

“…Due to the effectiveness of the proposed method on TikTok and MovieLens dataset with a recall of 0.590 and video label classification accuracy more than 94.9%, The approach demonstrates effective use of resources with a maximum CPU utilization of only 44% whilst maintaining high user satisfaction across different age groups. Overall, the results have an implication that the proposed approach can lead to better user interaction and satisfaction in a culturally diverse environment.…”
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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

“…Additionally, we analyze the impact of different IB parameters on the classification performance and provide insights into the optimal configuration for practical deployment. …”
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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

“…In our study, we’re discussing a way to solve this phenomenon by using Term Frequency-Inverse Document Frequency (TF-IDF) based approach to feature engineering on eleven classifiers for machine and deep learning that can automatically identify hate speech. Three different databases were used, the first of which “Hate speech offensive tweets by Davidson et al.”, the second called "Twitter hate speech" and finally we merged the second data with (Cyberbullying dataset (toxicity_parsed_dataset)". …”
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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

“…The proposed model is experimented with two different infrared thermography imaging datasets like DMR-IR and Proprietary Datasets. …”
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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

“…In addition, a Multi-Granularity Spatial Mamba Block is proposed, and this employs a multi-granularity scanning strategy to reduce the computational cost and feature redundancy on different scanning paths and is able to efficiently model the global contextual information of the target. …”
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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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