RB-TRNet: a regularity-guided and boundary-aware architecture for toponym recognition from Chinese text by Haigang Sui, Jindi Wang, Xining Zhang, Huihan Ning, Wentao Wang, Lieyun Hu

“…The CCPNT dataset, along with three other public datasets, were used for performance evaluation, and compared to eight baseline models, RB-TRNet exhibited state-of-the-art performance in recognizing complex Chinese place names.…”
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FBiLSTM-Attention short-term load forecasting based on fuzzy logic by Yan ZHANG, Zepeng KANG, Xiaozhi GAO, Nan YANG, Zhaolei WANG

“…Finally, the prediction results of the proposed method with traditional LSTM and BiLSTM Attention models were compared. The results show that the model combined with fuzzy logic has significantly improved accuracy and robustness, and has better predictive performance. …”
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CT texture analysis of pediatric teratomas—associations with identification and grading of immature teratoma by Xinxin Qi, Xiaoyu Wang, Wen Zhao, Songyu Teng, Guanglun Zhou, Hongwu Zeng

“…Comparisons of these features were performed between the IT and MT groups and within the IT groups. …”
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Sample selection using multi-task autoencoders in federated learning with non-IID data by Emre Ardıç, Yakup Genç

“…However, its performance is often hindered by redundant, malicious, or abnormal samples, leading to model degradation and inefficiency. …”
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Predictive analysis of pediatric gastroenteritis risk factors and seasonal variations using VGG Dense HybridNetClassifier a novel deep learning approach by P. T. Pranesh, Carmelin Durai Singh, Anand Sivanandam, Raman Muthusamy, Swati Sharma, Taha Alqahtani, Humood Al Shmrany, Daniel Ejim Uti

“…Further validation was performed by analyzing the model performance using one-way ANOVA and pairwise t-tests with several baselines such as SVM, Random Forest, and XGBoost. …”
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ECGNet: High-Precision ECG Classification Using Deep Learning and Advanced Activation Functions by Muhammad Abubakar, Ahsan Raza, Arfan Ali Nagra, Anas Bilal, Ahmad Alshammari, Monir Abdullah, Sahraoui Dhelim

“…ECGNet’s performance is compared with three benchmark deep learning models. …”
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AI-driven pharmacovigilance: Enhancing adverse drug reaction detection with deep learning and NLP by Dr. Bharti Khemani, Dr. Sachin Malave, Samyukta Shinde, Mandvi Shukla, Razzaq Shikalgar, Harshita Talwar

“…BERT and GPT, were also employed to provide the functionality of textual interactions over medical data. • Performance metrics such as accuracy, precision, recall, and F1-score were systematically applied to evaluate each model’s performance. …”
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A Preprocessing Method for Insulation Pull Rod Defect Dataset Based on the YOLOv5s Object Detection Network by Xuetong Li, Meng Cong, Bo Liu, Xianhao Fan, Weiqi Qin, Fangwei Liang, Chuanyang Li, Jinliang He

“…The results show that these two methods can specifically enhance small-sized defect targets while maintaining the detection performance for other types of targets. In contrast, the proposed method integrates copy–paste within images with Mosaic data augmentation and corrects bounding boxes for hair-like impurities significantly improving the model’s performance.…”
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INTEGRATION OF DISTRIBUTED INERTIAL NAVIGATION SYSTEMS BUILT AROUND FIBER-OPTIC AND MICROELECTROMECHANICAL SENSORS by A. V. Chernodarov, A. P. Patrikeev, I. I. Merkulova, S. I. Ivanov

“…The paper presents the results of fullscale experiments performed at the Ramenskoye Instrument-Making Plant.…”
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Transcriptome Derived Artificial neural networks predict PRRC2A as a potent biomarker for epilepsy by Wayez Naqvi, Prekshi Garg, Prachi Srivastava

“…The model’s performance was evaluated using the “pROC” R package, and an AUC of 0.720 was obtained, indicating that the model had excellent classification accuracy. …”
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Occupancy-Assisted Surround-View Images 3D Object Detection by Jian Sun

“…Additionally, when performing temporal modeling, I only interact with the occupied BEV features. …”
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A comprehensive case study of deep learning on the detection of alpha thalassemia and beta thalassemia using public and private datasets by Muhammad Umar Nasir, Muhammad Tahir Naseem, Taher M. Ghazal, Muhammad Zubair, Oualid Ali, Sagheer Abbas, Munir Ahmad, Khan Muhammad Adnan

“…Public datasets were sourced from medical databases, while private datasets were collected from clinical records, offering a more comprehensive feature set and larger sample sizes. After data preprocessing and splitting, model performance was evaluated. …”
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A Lightweight Neural Network for Cell Segmentation Based on Attention Enhancement by Shuang Xia, Qian Sun, Yiheng Zhou, Zhaoyuxuan Wang, Chaoxing You, Kainan Ma, Ming Liu

“…Experimental results on the PanNuke dataset demonstrate that AttE-Unet, despite its significant reduction in model size—with the number of parameters and floating-point operations per second reduced to 1.57% and 0.1% of the original model, respectively—still maintains a high level of segmentation performance. …”
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Double and integer multi-objective optimization of solar HDH desalination system with bubble column dehumidifier: An artificial neural network approach by Alireza Naeini, Alireza Jalali, Ehsan Houshfar

“…The gain output ratio (GOR) is selected to indicate the thermal performance, while the unit cost of water produced (UCWP) is chosen to reflect the economic performance. …”
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Impact of Image Preprocessing and Crack Type Distribution on YOLOv8-Based Road Crack Detection by Luxin Fan, Saihong Tang, Mohd Khairol Anuar b. Mohd Ariffin, Mohd Idris Shah Ismail, Xinming Wang

“…Furthermore, this study highlights that dataset balance significantly impacts model performance, as imbalanced datasets (CFD, Crack500, CrackTree200) led to biased predictions favoring dominant crack classes. …”
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Preliminary Design of Regional Aircraft—Integration of a Fuel Cell-Electric Energy Network in SUAVE by Jakob Schlittenhardt, Yannik Freund, Jonas Mangold, Richard Hanke-Rauschenbach, Andreas Strohmayer

“…For this, a reverse-engineered ATR 72-500 serves as a reference model for calibrating the methods and ensuring accurate performance modeling. …”
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Alzheimer’s disease risk prediction using machine learning for survival analysis with a comorbidity-based approach by Ferial Abuhantash, Roy Welsch, Stan Finkelstein, Aamna AlShehhi

“…The top features identified by the best-performing model include one demographic feature (age), seven cognitive scores (ADAS13, RAVLT learning, FAQ, ADAS11, RAVLT immediate, CDRSB, ADASQ4), and two comorbidities (Endocrine & Metabolic, Renal & Genitourinary). …”
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Enhancing the Prediction of Episodes of Aggression in Patients with Dementia Using Audio-Based Detection: A Multimodal Late Fusion Approach with a Meta-Classifier by Ioannis Galanakis, Rigas Filippos Soldatos, Nikitas Karanikolas, Athanasios Voulodimos, Ioannis Voyiatzis, Maria Samarakou

“…Various noise-filtering techniques were performed on the audio files using Mel-frequency cepstral coefficients (MFCCs), frequency filtering, and speech prosody to extract clear information from the audio features. …”
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Motion Classification With Embroidery Bend Sensors Using Multiple Zigzag-Stitch for Loose-Fitting Garments by Kaisei Minami, Yasuhiro Akiyama, Takuya Umedachi

“…Moreover, motion classification was performed by training a one-dimensional convolutional neural network (1D-CNN) model with the sensor signals. …”
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Reducing overfitting in vehicle recognition by decorrelated sparse representation regularisation by Wanyu Wei, Xinsha Fu, Siqi Ma, Yaqiao Zhu, Ning Lu

“…Abstract Most state‐of‐the‐art vehicle recognition methods benefit from the excellent feature extraction capabilities of convolutional neural networks (CNNs), which allow the models to perform well on the intra‐dataset. …”
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