Evaluating Features and Variations in Deepfake Videos Using the CoAtNet Model by Eman Alattas, John Clark, Arwa Al-Aama, Salma Kammoun Jarraya

“…Thus, in this study, we explore CoAtNet’s generalisation ability by conducting an extensive series of experiments with a focus on discovering features and variations in deepfake videos. These experiments involve training the model using various input and processing configurations, followed by evaluating its performance on widely recognised public datasets. …”
Get full text

A text classification model for dynamic fusion of global and local features by ZHENG Wenjun, ZHANG Shunxiang

“…Existing text classification models insufficiently utilize global and local information in texts, leading to subpar classification performance. …”
Get full text

Re-identification of patients from imaging features extracted by foundation models by Giacomo Nebbia, Sourav Kumar, Stephen Michael McNamara, Christopher Bridge, J. Peter Campbell, Michael F. Chiang, Naresh Mandava, Praveer Singh, Jayashree Kalpathy-Cramer

“…Abstract Foundation models for medical imaging are a prominent research topic, but risks associated with the imaging features they can capture have not been explored. …”
Get full text

Prediction model for chemical explosion consequences via multimodal feature fusion by Yilin Wang, Beibei Wang, Yichen Zhang, Jiquan Zhang, Yijie Song, Shuang-Hua Yang

“…A comprehensive validation and evaluation of the constructed model were performed. Results demonstrate that the optimized Bayes-Transformer-SVM model achieves superior performance, with test set metrics reaching an R2 of 0.9475 and RMSE of 0.1139, outperforming alternative prediction models. …”
Get full text

MFEAM: Multi-View Feature Enhanced Attention Model for Image Captioning by Yang Cui, Juan Zhang

“…In this paper, we propose MFEAM, an innovative network that leverages the multi-view feature enhanced attention. To accurately represent the entangled features of vision and text, the teacher model employs the multi-view feature enhanced attention to guide the student model training through knowledge distillation and model averaging from both visual and textual views. …”
Get full text

New Approaches of Stochastic Models to Examine the Vibration Features in Roller Bearings by Saima Bhatti, Asif Ali Shaikh, Asif Mansoor, Murtaza Hussain

“…These models, developed separately for inner and outer race fault features in comparison to healthy bearing features under random conditions, offer valuable insights into machinery prognosis. …”
Get full text

Optimizing Power Forecasting Models with Customized Features for Academic and Industrial Buildings by David Cabezuelo, Izar Lopez-Ramirez, June Urkizu, Ander Goikoetxea

“…Our analysis reveals that higher data collection frequency generally improves model performance, as indicated by lower RMSE, MAPE, and CV values, alongside higher R² scores. …”
Get full text

An ensemble deep learning model for author identification through multiple features by Yuan Zhang

“…More importantly, a self-attention mechanism is presented to smartly combine the results of these specialized CNNs so that the model can dynamically learn the significance of each type of features. …”
Get full text

Graph Attention Neural Network Model With Behavior Features for Knowledge Tracking by Wei Zhang, Sen Hu, Kaiyuan Qu

“…The existing deep knowledge tracking models ignore the students’ behavior features and the high-order relationship between and questions with overlapping skills in the learning process. …”
Get full text

Features of development and analysis of the simulation model of a multiprocessor computer system by O. M. Brekhov, G. A. Zvonareva, V. V. Ryabov

“…The article considers the features of the development of the simulation model for estimating the time characteristics of a multiprocessor computer system, as well as the use of the regenerative method of model analysis. …”
Get full text

CFS-MOES Ensemble Model on Metaheuristic Search-Based Feature Selection by Santosini Bhutia, Bichitrananda Patra, Mitrabinda Ray

“…Furthermore, a CFS-MOES (correlation-based feature selection—multiobject evolutionary search) ensemble model is proposed based on a majority voting mechanism to improve the classification performance. …”
Get full text

An optimized ensemble model with advanced feature selection for network intrusion detection by Afaq Ahmed, Muhammad Asim, Irshad Ullah, Zainulabidin, Abdelhamied A. Ateya

“…We conducted a comprehensive evaluation of the proposed approach against several well-known machine learning models, including AdaBoostM1 (AbM1), K-nearest neighbor (KNN), J48-Decision Tree (J48), multilayer perceptron (MLP), stochastic gradient descent (SGD), naïve Bayes (NB), and logistic model tree (LMT). …”
Get full text

Feature Extraction and Analysis Method of Trombone Timbre Based on CNN Model by Yanjun Wang

“…Finally, the simulation results show that the trombone timbre feature extraction method based on the CNN model proposed in this paper can effectively identify the trombone timbre in various musical performances.…”
Get full text

A Multi-Path Feature Extraction and Transformer Feature Enhancement DEM Super-Resolution Reconstruction Network by Mingqiang Guo, Feng Xiong, Ying Huang, Zhizheng Zhang, Jiaming Zhang

“…Through repeated testing and improvement, the model shows excellent performance in high-resolution DEM image reconstruction, and can generate more accurate DEMs. …”
Get full text

Insights into gait performance in Parkinson's disease via latent features of deep graph neural networks by Jiecheng Wu, Jiecheng Wu, Ning Su, Xinjin Li, Xinjin Li, Chao Yao, Jipeng Zhang, Xucheng Zhang, Wei Sun

“…However, most of the current methods depend on data preprocessing and feature engineering, often require domain knowledge and laborious human involvement, and require additional manual adjustments when dealing with new tasks.MethodsTo reduce the model's reliance on data preprocessing, feature engineering, and traversal rules, we employed the Spatial-Temporal Graph Convolutional Networks (ST-GCN) model. …”
Get full text

Melonic limits of the quartic Yukawa model and general features of melonic CFTs by Ludo Fraser-Taliente, John Wheater

“…Abstract We study a set of large-N tensor field theories with a rich structure of fixed points, encompassing both the melonic and prismatic CFTs observed previously in the conformal limits of other tensor theories and in the generalised Sachdev-Ye-Kitaev (SYK) model. The tensor fields interact via an O(N)3-invariant generalisation of the quartic Yukawa model, ϕ 2 ψ ¯ ψ $$ {\phi}^2\overline{\psi}\psi $$ + ϕ 6. …”
Get full text

DBRSNet: a dual-branch remote sensing image segmentation model based on feature interaction and multi-scale feature fusion by Yong Ji, Wenbin Shi, Jingsheng Lei, Jiayin Ding

“…Extensive evaluations on the ISPRS Vaihingen and ISPRS Potsdam datasets validate that DBRSNet surpasses 14 cutting-edge remote sensing segmentation models across all assessment metrics, highlighting its exceptional performance and competitiveness.…”
Get full text

A Method for Prediction and Analysis of Student Performance That Combines Multi-Dimensional Features of Time and Space by Zheng Luo, Jiahao Mai, Caihong Feng, Deyao Kong, Jingyu Liu, Yunhong Ding, Bo Qi, Zhanbo Zhu

“…Therefore, a student performance prediction and analysis method incorporating multidimensional spatiotemporal features has been proposed in this study. …”
Get full text

A fine-grained human facial key feature extraction and fusion method for emotion recognition by Shiwei Li, Jisen Wang, Linbo Tian, Jianqiang Wang, Yan Huang

“…Compared to existing state-of-the-art models, our refined face feature extraction and fusion model demonstrates superior performance in emotion recognition. …”
Get full text

Comparisons of Faulting-Based Pavement Performance Prediction Models by Weina Wang, Yu Qin, Xiaofei Li, Di Wang, Huiqiang Chen

“…This paper reviews performance prediction models and JPCP faulting models that have been used in past research. …”
Get full text