Advancing breast cancer diagnosis: token vision transformers for faster and accurate classification of histopathology images by Mouhamed Laid Abimouloud, Khaled Bensid, Mohamed Elleuch, Mohamed Ben Ammar, Monji Kherallah

“…ViTs are notably recognized for their complex architecture, which requires high-performance GPUs or CPUs for efficient model training and deployment in real-world medical diagnostic devices. …”
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Enhanced Segmentation of Glioma Subregions via Modality-Aware Encoding and Channel-Wise Attention in Multimodal MRI by Annachiara Cariola, Elena Sibilano, Antonio Brunetti, Domenico Buongiorno, Andrea Guerriero, Vitoantonio Bevilacqua

“…The statistically significant improvements obtained on all regions highlight the effectiveness of integrating complementary modality-specific information and applying channel-wise feature recalibration in the proposed model.…”
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Classification Prediction of Jujube Variety Based on Hyperspectral Imaging: A Comparative Study of Intelligent Optimization Algorithms by Quancheng Liu, Jun Zhou, Zhaoyi Wu, Didi Ma, Yuxuan Ma, Shuxiang Fan, Lei Yan

“…The GWO-SVM-SG1st model achieved the highest classification accuracy, with 94.641% on the prediction sets. …”
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Pipe Resistance Loss Calculation in Industry 4.0: An Innovative Framework Based on TransKAN and Generative AI by Qinyu Zhang, Huiying Liu, Zhike Liu, Yongkang Liu, Yuhan Gong, Chonghao Wang

“…The experimental data collected from pipeline pressure sensors provides empirical validation for the model. Compared with traditional mathematical formulas, BP neural networks, SVMs, and random forests, the proposed model demonstrates superior performance, achieving an R² value of 0.9644, an RMSE of 0.7126, and an MAE of 0.4703.…”
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Tensor-Based Uncoupled and Incomplete Multi-View Clustering by Yapeng Liu, Wei Guo, Weiyu Li, Jingfeng Su, Qianlong Zhou, Shanshan Yu

“…An efficient algorithm is designed to solve the proposed model. Experimental results on five widely used benchmark datasets show that the proposed method exhibits superior clustering performance on incomplete and uncoupled multi-view data.…”
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Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation by Yike Li, Mingyang Xiao, Yaqian Li, Lulu Lv, Shanshan Zhang, Yuhui Liu, Juan Zhang

“…The 6 models were compared in the testing set to identify the best-performing model. …”
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Novel mRNA biomarker-based liquid biopsy for the detection of resectable pancreatic cancer by Jong-chan Lee, Sung Won Kang, Eun-Jin Sim, Jin-Sik Bae, Seong-mo Koo, Mun-sub Byoun, Serin Kwon, Seoi Hong, Yunji Kim, Yuna Youn, Kwangrok Jung, Jaihwan Kim, Hyoung Hwa Jeong, Jihie Kim, Jin-Hyeok Hwang

“…Machine learning-based feature selection confirmed the final biomarker panel, which was tested using an independent dataset for diagnostic performance. …”
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Urban Sprawl Monitoring by VHR Images Using Active Contour Loss and Improved U-Net with Mix Transformer Encoders by Miguel Chicchon, Francesca Colosi, Eva Savina Malinverni, Francisco James León Trujillo

“…Quantitative results showed that the U-Net-scse model with an MiTB5 encoder achieved the best performance with respect to SegFormer and FT-UNet-Former, with IoU scores of 0.8288 on OpenEarthMap and 0.6743 on Chan Chan images. …”
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Excavation of gene markers associated with pancreatic ductal adenocarcinoma based on interrelationships of gene expression by Zhao‐Yue Zhang, Zi‐Jie Sun, Dong Gao, Yu‐Duo Hao, Hao Lin, Fen Liu

“…Using incremental feature selection, the authors refined the selected gene set and constructed a machine‐learning model for PDAC recognition. …”
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An advanced real-time crash prediction framework for combined hard shoulder running and variable speed limits system using transformer by Mohamed Abdel-Aty, Tarek Hasan, B M Tazbiul Hassan Anik

“…Additionally, the results indicate substantial improvements in model prediction performance (i.e., an increment of sensitivity values by 7.04% and 8.33% in the AM and PM models, respectively) after incorporating the general safety condition of a freeway segment as an input feature while estimating real-time crash prediction models. …”
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STT-Net: Simplified Temporal Transformer for Emotion Recognition by Mustaqeem Khan, Abdulmotaleb El Saddik, Mohamed Deriche, Wail Gueaieb

“…To that end, we studied temporal feature shifting for frame-wise deep learning models to avoid this burden. …”
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Research and optimization of a multilevel fire detection framework based on deep learning and classical pattern recognition techniques by Qi Liu, Hong Chen, Da Lin

“…The experimental results demonstrate the exceptional performance of the model, achieving precision, recall, F1 score, and accuracy rates of 98.23%, 96.33%, 97.33%, and 95.08%, respectively, on the Dataset for Fire and Smoke Detection (DFS), substantially surpassing existing methods. …”
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Text-Conditioned Diffusion-Based Synthetic Data Generation for Turbine Engine Sensor Analysis and RUL Estimation by Luis Pablo Mora-de-León, David Solís-Martín, Juan Galán-Páez, Joaquín Borrego-Díaz

“…This paper introduces a novel framework for generating synthetic time-series data from turbine engine sensor readings using a text-conditioned diffusion model. The approach begins with dataset preprocessing, including correlation analysis, feature selection, and normalization. …”
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LE-YOLOv5: A Lightweight and Efficient Neural Network for Steel Surface Defect Detection by Chengshun Zhu, Yong Sun, Hongji Zhang, Shilong Yuan, Hui Zhang

“…Finally, we design a global coordination attention (GCA) to efficiently connect position and spatial information from the feature map. Numerous experimental results demonstrate that LE-YOLOv5 has a highly superior overall performance, reaching 79.1% mean Average Precision (mAP) on the NEU-DET dataset while inferring an image on the CPU in 196.1 ms, which is 5% and 1.5% improved mAP compared to YOLOv5M and YOLOv5L, respectively. …”
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SSD-YOLO: a lightweight network for rice leaf disease detection by Canlin Pan, Shen Wang, Shen Wang, Yahui Wang, Chaoyang Liu

“…Furthermore, Shape-aware Intersection over Union (ShapeIoU) Loss replaces the traditional Complete Intersection over Union (CIoU) loss function, boosting model performance in complex environments. We constructed a dataset of 3000 rice leaf disease images for experimental validation of the SSD-YOLO model. …”
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Torsional Vibration Characterization of Hybrid Power Systems via Disturbance Observer and Partitioned Learning by Tao Zheng, Hui Xie, Boqiang Liang

“…A simplified model of the drivetrain shaft system is first established, and an extended state Kalman filter (ESKF) is designed to accurately estimate the torque of the torsional damper. …”
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Siamese network with change awareness for surface defect segmentation in complex backgrounds by Biyuan Liu, Sijie Luo, Huiyao Zhan, Yicheng Zhou, Zhou Huang, Huaixin Chen

“…Furthermore, our model achieves a new state-of-the-art performance compared to semi-supervised approaches across various supervision settings. …”
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User preference information recommendation based on DCGNN and GNNPK algorithms by Nannan Cheng, Xiaoyang He

“…It can be seen from this that the proposed recommendation model performs well in handling user preference information. …”
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Enhancing mixing efficiency in multi-impeller tanks through innovative CFD and artificial neural network approaches by Reza Beigzadeh, Saber Soltanian, Yousef Azizpour

“…The ANN model shows strong predictive performance with a mean relative error of 2.45 %, confirming its accuracy for this application. …”
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BLS-QLSTM: a novel hybrid quantum neural network for stock index forecasting by Liyun Su, Dan Li, Dongyang Qiu

“…Although some existing machine learning methods and deep learning models perform well in certain cases, they still face limitations in handling high-dimensional data and time dependencies. …”
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