PoulTrans: a transformer-based model for accurate poultry condition assessment by Jun Li, Bing Yang, Junyang Chen, Jiaxin Liu, Felix Kwame Amevor, Guanyu Chen, Buyuan Zhang, Xiaoling Zhao

“…To address this, we present PoulTrans, an innovative image captioning framework that leverages a Convolutional Neural Network (CNN) integrated with a CSA_Encoder-Transformer architecture to generate detailed poultry status reports. This model incorporates visual features extracted by CNNs into the Channel Spatial Attention Segmentation Encoder (CSA_Encoder), which produces segmented channel and spatial attention outputs. …”
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GDFC-YOLO: An Efficient Perception Detection Model for Precise Wheat Disease Recognition by Jiawei Qian, Chenxu Dai, Zhanlin Ji, Jinyun Liu

“…However, at present, its detection accuracy still has certain limitations. The existing models hardly capture the irregular and fine-grained texture features of the lesions, and the results of spatial information reconstruction caused by standard upsampling operations are inaccuracy. …”
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Two stream GRU model with ELU activation function for sign language recognition by Kasian Myagila, Devotha Godfrey Nyambo, Mussa Ally Dida

“…Additionally, the results indicate that, the proposed model can have a positive impact on limited computational resources while also enhancing the model’s overall performance.…”
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Scenario modeling of the drug prescription process for children: application of machine learning methods by А. А. Kondrashov, М. М. Kurashov, Е. Е. Loskutova

“…Objective: determining the most appropriate machine learning method to solve the problem of drug prescribtion for children, evaluating its performance and potential for implementation into scenario modeling systems of the pharmaceutical care structure.Material and methods. …”
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Metro Station Passenger Volume Prediction Algorithm Based on Improved LSTNet Model by XU Ling, GUAN Jianbo, XU Xiwei, BAN Yong

“…Based on the prediction results, the performance of the improved LSTNet model is evaluated. …”
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Category Management Methods as a Basis for organizing a Balanced Procurement Model by A. M. Levandovskaia

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Autocorrelation Matrix Knowledge Distillation: A Task-Specific Distillation Method for BERT Models by Kai Zhang, Jinqiu Li, Bingqian Wang, Haoran Meng

“…The AMKD method effectively captures the relationships between features using the autocorrelation matrix, enabling the student model to learn not only the performance of individual features from the teacher model but also the correlations among these features. …”
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A machine learning-based risk prediction model for diabetic oral ulceration by Wang Xiaoling, Wang BingQian, Zhu Zhenqi, Li Wen, Gu Shuyan, Chen Hanbei, Xin Feng, Chenglong Yang, Jutang li, Guoyao Tang, Jie Wei

“…The dataset included 324 diabetic patients, with 127 DOU features. One-hundred-fold cross-validation was employed for model optimization and feature selection. …”
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Research and Experiment on a Chickweed Identification Model Based on Improved YOLOv5s by Hong Yu, Jie Zhao, Xiaobo Xi, Yongbo Li, Ying Zhao

“…In response to the above problems, using chickweed as the identification object, a weed identification model based on improved YOLOv5s was proposed. Firstly, the Squeeze-and-Excitation Module (SE) and Convolutional Block Attention Module (CBAM) were added to the model’s feature extraction network to improve the model’s recognition accuracy; secondly, the Ghost convolution lightweight feature fusion network was introduced to effectively identify the volume, parameter amount, and calculation amount of the model, and make the model lightweight; finally, we replaced the loss function in the original target bounding box with the Efficient Intersection over Union (EloU) loss function to further improve the detection performance of the improved YOLOv5s model. …”
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Named Entity Recognition Model Based on the Fusion of Word Vectors and Category Vectors by Yang Zhou, Haoyang Zeng, Wei Zhang, Yuguang Zhang

“…Validation on three NER datasets&#x2014;Weibo, Youku, and Chinese literature&#x2014;demonstrates that the proposed model is both feasible and effective. Compared to a baseline model that solely relies on word vectors, the proposed model exhibits enhanced NER performance, achieving improvements in <inline-formula> <tex-math notation="LaTeX">$F1$ </tex-math></inline-formula> scores by 5.05%, 1.53%, and 1.81% respectively on the Weibo, Youku, and Chinese literature datasets.…”
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An Attention-based Model for Recognition of Facial Expressions Using CNN-BiLSTM by Sushil Kumar Singh, Manish Kumar, Ikram Majeed Khan, A. Jayanthiladevi, Chirag Agarwal

“…To address the challenges posed by non-frontal visual features, this study proposes a hybrid model that fusion of Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (BiLSTM), augmented with a point multiplication attention model and Linear Discriminant Analysis (LDA). …”
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ASHM-YOLOv9: A Detection Model for Strawberry in Greenhouses at Multiple Stages by Yan Mo, Shaowei Bai, Wei Chen

“…The parameters, model size, and floating-point calculations were reduced by 3.7%, 5.6% and 3.8%, respectively, which significantly boosted the performance of the original model and outperformed that of the other models. …”
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Simultaneous Learning Knowledge Distillation for Image Restoration: Efficient Model Compression for Drones by Yongheng Zhang

“…Deploying high-performance image restoration models on drones is critical for applications like autonomous navigation, surveillance, and environmental monitoring. …”
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Advanced Trans-BiGRU-QA Fusion Model for Atmospheric Mercury Prediction by Dong-Her Shih, Feng-I. Chung, Ting-Wei Wu, Bo-Hao Wang, Ming-Hung Shih

“…This study utilizes air quality data from Vietnam to train and test the models, evaluating their performance in predicting atmospheric mercury concentration. …”
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OPTNet: Optimized Pixel-Transformer Model for Adaptive Retinal Fundus Image Enhancement by Faisal Majed Alqahtani, Somaya Adwan, Mohd Yazed Ahmad, Salmah Binti Karman

“…The proposed approach consists of three main stages: 1) pre-processing to standardize image dimensions and balance color channels, 2) model development, in which a lightweight ANN-based feature extractor learns retinal structures and generates self-measured quality labels, and 3) pixel-level transformation guided by these predicted labels to perform localized enhancement. …”
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Intent-aware knowledge graph-based model for electrical power material recommendation by Lin Zhao, Ning Luan, Weihua Cheng, Shuming Feng, Hui Wang, Yongcheng Yang, Guixiang Zhu

“…Finally, an adaptive fusion with attention network is devised to generate comprehensive user representation by integrating user preference and intent features. Extensive experiments conducted on the real-life electric power materials show that our proposed model outperforms state-of-the-art methods.…”
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Advanced intelligent techniques for modeling oxygen storage in zeolite-based porous materials by Arefeh Naghizadeh, Ahmadreza Jafari-Sirizi, Behnam Amiri-Ramsheh, Saeid Atashrouz, Dragutin Nedeljkovic, Ahmad Mohaddespour, Abdolhossein Hemmati-Sarapardeh

“…A comprehensive database of 750 experimental O2 uptake values was constructed, incorporating pressure, pore volume, temperature, and surface area as input features to develop robust predictive models. The findings demonstrated the superior performance of the GRNN model, achieving an exceptional root mean square error of 0.03 and a coefficient of determination (R2) of 0.9991, outperforming the other techniques. …”
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Swin-PSO-SVM: A Novel Hybrid Model for Monkeypox Early Detection by Hager Saleh, Sherif Mostafa, Alshimaa H. Ismail, Sumit Srivastava, Saeed Hamood Alsamhi

“…We introduce a novel hybrid Swin-PSO-SVM to improve the precision and dependability of monkeypox detection. The Swin-PSO-SVM model incorporates a Swin Transformer for complex feature extraction, Particle Swarm Optimization (PSO) for extracting the best features from complex feature extraction, and a Support Vector Machine (SVM) for accurate classification. …”
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An Efficient 3D Model Retrieval Method Based on Convolutional Neural Network by Bo Ding, Lei Tang, Yong-jun He

“…In retrieval, the 2D views of the input model are classified into a category with the CNN and voting algorithm, and then only the features of one category rather than all categories are chosen to perform similarity matching. …”
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Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

“…After determining the network hyperparameters, ablation experiments were conducted to analyze the contribution of each strategy to the network model, providing a clear understanding of how each strategy impacts prediction performance. …”
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