Attention-Based Hypergraph Neural Network: A Personalized Recommendation by Peihua Xu, Maoyuan Zhang

“…By constructing a heterogeneous hypergraph structure encompassing three entity types (students, instructors, and courses), we innovatively designed hypergraph convolution operators to achieve bidirectional vertex-hyperedge information aggregation, integrated with a dynamic attention mechanism to quantify important differences among entities. …”
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TCSRNet: a lightweight tobacco leaf curing stage recognition network model by Panzhen Zhao, Panzhen Zhao, Songfeng Wang, Shijiang Duan, Aihua Wang, Lingfeng Meng, Yichong Hu

“…Firstly, the model utilizes an Inception structure with parallel convolutional branches to capture features at different receptive fields, thereby better adapting to the appearance variations of tobacco leaves at different curing stages. …”
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Comprehensive Multi-indicator Prediction Model for Storage Quality of Multi-cultivar Kiwifruit Based on Visible-Near Infrared Spectroscopy by Zizhao LIANG, Xin LI, Pu LIU, Wenqiang GUAN, Ming LI

“…After the use of different preprocessing algorithms, such as first-order derivatives (FD), standard normal variate (SNV), second-order derivatives, convolutional smoothing, and FD+SNV, the data were combined with competitive adaptive reweighted sampling (CARS) for feature wavelength selection. …”
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Galaxy Morphological Classification with Zernike Moments and Machine Learning Approaches by Hamed Ghaderi, Nasibe Alipour, Hossein Safari

“…The uniqueness due to the orthogonality and completeness of Zernike polynomials, reconstruction of the original images with minimum errors, invariances (rotation, translation, and scaling), different block structures, and discriminant decision boundaries of ZMs’ probability density functions for different order numbers indicate the capability of ZMs in describing galaxy features. …”
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A Fog Computing-Based Cost-Effective Smart Health Monitoring Device for Infectious Disease Applications by Saranya Govindakumar, Vijayalakshmi Sankaran, Paramasivam Alagumariappan, Bhaskar Kosuru Bojji Raju, Daniel Ford

“…Further, the proposed device consists of three different biosensor modules, namely a MAX90614 infrared temperature sensor, a MAX30100 pulse oximeter, and a microphone sensor. …”
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Stealthy Adversarial Attacks on Machine Learning-Based Classifiers of Wireless Signals by Wenhan Zhang, Marwan Krunz, Gregory Ditzler

“…Specifically, we consider several exemplary protocol and modulation classifiers, designed using convolutional neural networks (CNNs) and recurrent neural networks (RNNs). …”
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Toward AI-Driven Cough Sound Analysis for Respiratory Disease Diagnosis by Houda Benaliouche, Houda Hafi, Hakim Bendjenna, Zeyad Alshaikh

“…Our study involves the application of three distinct models: a Convolutional Neural Network (CNN) model, a CNN-Support Vector Machine (CNN-SVM) hybrid model, and a transfer learning-based model. …”
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The evaluation model of engineering practice teaching with complex network analytic hierarchy process based on deep learning by Xianlong Han, Xiaohui Chen

“…Through the hierarchical analysis of complex network, the relationship between different teaching elements is revealed and the hierarchical structure is constructed. …”
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Liver Semantic Segmentation Method Based on Multi-Channel Feature Extraction and Cross Fusion by Chenghao Zhang, Lingfei Wang, Chunyu Zhang, Yu Zhang, Peng Wang, Jin Li

“…Firstly, a multi-scale input strategy is employed to account for the variability in liver features at different scales. A multi-scale convolutional attention (MSCA) mechanism is integrated into the encoder to aggregate multi-scale information and improve feature representation. …”
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Traceability of Rizhao green tea origin based on multispectral data fusion strategy and chemometrics by Mengqi Guo, Zhiwei Chen, Zezhong Ding, Dewen Wang, Dandan Qi, Min Lu, Mei Wang, Chunwang Dong

“…The study found significant spectral differences in tea samples from different regions, leading to robust differentiation. …”
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RMVAD-YOLO: A Robust Multi-View Aircraft Detection Model for Imbalanced and Similar Classes by Keda Li, Xiangyue Zheng, Jingxin Bi, Gang Zhang, Yi Cui, Tao Lei

“…First, we propose a novel Robust Multi-Link Scale Interactive Feature Pyramid Network (RMSFPN), which robustly extracts features of the same aircraft category from multiple views while enhancing feature differentiation between different aircraft categories. Second, we propose the Shared Convolutional Dynamic Alignment Detection Head (SCDADH), which enhances task interaction and collaboration by sharing convolutions between the classification and localization branches while simultaneously reducing the number of parameters, enhancing the model’s ability to deal with multi-scale targets. …”
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XCF-LSTMSATNet: A Classification Approach for EEG Signals Evoked by Dynamic Random Dot Stereograms by Tingting Zhang, Xu Yan, Xin Chen, Yi Mao

“…Stereovision is the visual perception of depth derived from the integration of two slightly different images from each eye, enabling understanding of the three-dimensional space. …”
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Autonomous International Classification of Diseases Coding Using Pretrained Language Models and Advanced Prompt Learning Techniques: Evaluation of an Automated Analysis System Usin... by Yan Zhuang, Junyan Zhang, Xiuxing Li, Chao Liu, Yue Yu, Wei Dong, Kunlun He

“…Additionally, we evaluated the framework’s performance under different prompt learning and fine-tuning settings. …”
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BESW-YOLO: A Lightweight SAR Image Detection Model Based on YOLOv8n for Complex Scenarios by Xiao Tang, Kun Cao, Yunzhi Xia, Enkun Cui, Weining Zhao, Qiong Chen

“…First, we introduce a novel lightweight feature pyramid network, bidirectional and multiscale attention feature pyramid network, which effectively enhances the fusion of features across different scales. Second, efficient multiscale convolution (EMSC) is introduced, which is combined with the C2f module in the YOLO model to form a new module, EMSC-C2f. …”
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LAVID: A Lightweight and Autonomous Smart Camera System for Urban Violence Detection and Geolocation by Mohammed Azzakhnini, Houda Saidi, Ahmed Azough, Hamid Tairi, Hassan Qjidaa

“…Our proposed system, named LAVID, is based on a depthwise separable convolution model (DSCNN) combined with a bidirectional long-short-term memory network (BiLSTM) and implemented on a lightweight smart camera. …”
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Detection of cyber attacks in electric vehicle charging systems using a remaining useful life generative adversarial network by Hayriye Tanyıldız, Canan Batur Şahin, Özlem Batur Dinler, Hazem Migdady, Kashif Saleem, Aseel Smerat, Amir H. Gandomi, Laith Abualigah

“…Furthermore, we assess the prediction results of different deep learning models, such as gated recurrent units (GRUs), long short-term memory (LSTM), recurrent neural networks (RNNs), convolution neural networks (CNNs), multi-layer perceptron (MLP), and dense layer integrated with generative adversarial networks (GANs), using mean absolute error (MAE), root mean square error (RMSE), mean squared error (MSE), and R-squared (R2). …”
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Estimating actual crop evapotranspiration by using satellite images coupled with hybrid deep learning-based models in potato fields by Larona Keabetswe, Yiyin He, Chao Li, Zhenjiang Zhou

“…Motivated by the robustness of deep learning models, this study employed two hybrid models that integrate Convolution Neural Network with either Random Forests (CNN-RF) or Support Vector Machine (CNN-SVR) to estimate potato ETc act using a limited set of input features. …”
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Mapping stains on flat roofs using semantic segmentation based on deep learning by Lara Monalisa Alves dos Santos, Leonardo Rabero Lescano, Gabriel Toshio Hirokawa Higa, Vanda Alice Garcia Zanoni, Lenildo Santos da Silva, Cesar Ivan Alvarez, Hemerson Pistori

“…The research tested two convolutional neural networks for semantic segmentation: the Fully Convolutional Network (FCN) with a ResNet50 backbone and DeepLabV3 with a ResNet101 backbone, as well as a transformer-based deep artificial neural network called SegFormer with a MiT-B1 backbone. …”
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Multi-scale CNN-CrossViT network for offline handwritten signature recognition and verification by Wanying Li, Mahpirat Muhammat, Xuebin Xu, Alimjan Aysa, Kurban Ubul

“…Abstract Developing technologies that can accurately identify and highlight subtle differences in signatures is crucial for improving the performance of signature recognition and verification. …”
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KANDiff: Kolmogorov–Arnold Network and Diffusion Model-Based Network for Hyperspectral and Multispectral Image Fusion by Wei Li, Lu Li, Man Peng, Ran Tao

“…Furthermore, the image generated by the diffusion model may exhibit a small amount of the remaining noise. Convolutional Neural Networks (CNNs) effectively extract local features through their convolutional layers and achieve noise suppression via layer-by-layer feature representation. …”
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