Integrating the Prior Shape Knowledge Into Deep Model and Feature Fusion for Topologically Effective Brain Tumor Segmentation by Salma Asif, Ahmad Raza Shahid, Kiran Aftab, Syed Ather Enam

“…However, deep learning models prioritize either local or global features, failing to adequately capture topological features or integrate prior shape knowledge. …”
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Establishment of nomogram prediction model for patients with chronic obstructive pulmonary disease based on Lasso feature screening by Shuyi Zhang, Jiaojiao Sha, Tao Jiang, Zhou Lu, Yulin Shi, Jiatuo Xu

“…Background and objective To establish a nomogram prediction model for patients with chronic obstructive pulmonary disease (COPD) based on Lasso feature screening using acoustic features and general clinical data, as well as a risk warning model for patients with acute exacerbation of COPD (AECOPD), and to investigate the performance and value of these two models. …”
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Physicomathematical modeling of the formation features of fillet welds of bridge metal structures under submerged-arc welding by A. A. Mosin, V. A. Erofeev, M. A. Sholokhov

“…New mathematical relationships that describe physical phenomena under the submerged-arc welding of fillet welds are proposed. The key feature of the proposed model is in the fundamental difference between the submerged-arc welding and the gas-shielded arc welding, i.e., during submerged-arc welding, the arc burns in a gas-vapor cavern that appears due to the melting and evaporation of flux. …”
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Construction and Application of Feature Recommendation Model for Remote Sensing Interpretation of Rock Strata Based on Knowledge Graph by Liufeng Tao, Qirui Wu, Miao Tian, Zhong Xie, Jianguo Chen, Yueyu Wu, Qinjun Qiu

“…Using a dataset of 2591 geological survey reports and scientific literature, a remote sensing interpretation ontology model was established, featuring four core entities (rock type, stratigraphic unit, spectral feature, and geomorphological indicator). …”
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A Rotated Object Detection Model With Feature Redundancy Optimization for Coronary Athero-Sclerotic Plaque Detection by Xue Hao, Haza Nuzly Abdull Hamed, Qichen Su, Xin Dai, Linqiang Deng

“…Current methods for addressing redundant features rely mostly on simple feature selection or reduction methods, overlooking the significance of redundant features in model training. …”
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Agricultural Text Classification Method Based on ERNIE 2.0 and Multi-Feature Dynamic Fusion by Xuliang Duan, Yuhai Liu, Zhenjia You, Zhiyao Li

“…With the introduction of an attention mechanism, the model can dynamically adjust feature weights to achieve effective multi-feature fusion. …”
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Prediction of the Trimer Protein Interface Residue Pair by CNN-GRU Model Based on Multi-Feature Map by Yanfen Lyu, Ting Xiong, Shuaibo Shi, Dong Wang, Xueqing Yang, Qihuan Liu, Zhengtan Li, Zhixin Li, Chunxia Wang, Ruiai Chen

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Features of simulation of operator control of unmanned aerial vehicle and its target load by P. I. Savelov, Penghao Gu, A. A. Lobaty

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Wetland Scene Segmentation of Remote Sensing Images Based on Lie Group Feature and Graph Cut Model by Canyu Chen, Guobin Zhu, Xiliang Chen

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Evaluation of Feature Selection and Regression Models to Predict Biomass of Sweet Basil by Using Drone and Satellite Imagery by Luana Centorame, Nicolò La Porta, Michela Papandrea, Adriano Mancini, Ester Foppa Pedretti

“…A dataset of 40 sampling points was built by combining remote sensing data with field measurements, and seven vegetation indices were calculated for each point. Feature selection was performed using three different methods (F-score, Recursive Feature Elimination, and model-based selection), and the most informative features were then processed through Principal Component Analysis. …”
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EML-SlowFast: A behavior recognition model for lion-head goose by Jinwei Wang, Zhiguo Du, Bin Wen, Zhihui Wu, Xudong Lin

“…The Efficient Channel Attention Bottleneck (ECAbneck) module and the Large Kernel Global-Local Feature Extraction (LGLE) module are designed and incorporated into the model. …”
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Brain Tumour Detection Using VGG-Based Feature Extraction With Modified DarkNet-53 Model by S. Trisheela, Roshan Fernandes, Anisha P. Rodrigues, S. Supreeth, B. J. Ambika, Piyush Kumar Pareek, Rakesh Kumar Godi, G. Shruthi

“…We propose a modified DarkNet-53 architecture, optimized with invasive weed optimization (IWO), to extract critical features from preprocessed MRI images. The model’s presentation is assessed using accuracy, recall, loss, and AUC, achieving a 95% success rate on a dataset of 3264 MRI scans. …”
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Classification of Ship Type from Combination of HMM–DNN–CNN Models Based on Ship Trajectory Features by Dae-Woon Shin, Chan-Su Yang

“…The HMM–DNN–CNN combination was obtained as the optimal model (average F-1 score: 97.54%), achieving individual classification performances of 99.03%, 97.46%, and 95.83% for fishing boats, passenger ships, and container ships, respectively. …”
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Enhancing heart disease prediction accuracy by comparing classification models employing varied feature selection techniques by Balliu Lorena, Zanaj Blerina, Basha Gledis, Zanaj Elma, Meçe Elinda Kajo

“…This results in SVM and RM performing better after applying feature selection for individual ML models. …”
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Peculiar structural features of the metacognitive subsystem of mental models of interactions of servicemen of the National Guard of the Russian Federation by Fedorishin, Michael Ivanovich, Perevozkina, Yulia M.

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Performance Evaluation of Different Speech-Based Emotional Stress Level Detection Approaches by Jan Stas, Stanislav Ondas, Jozef Juhar

“…These results highlight the importance of robust feature selection, appropriate classifier design, and the integration of emotional speech data to enhance generalization performance in real-world applications.…”
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Development of a Student Depression Prediction Model Based on Machine Learning with Algorithm Performance Evaluation by Penni Wintasari Simarmata, Putri Taqwa Prasetyaningrum

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LPFFNet: Lightweight Prior Feature Fusion Network for SAR Ship Detection by Xiaozhen Ren, Peiyuan Zhou, Xiaqiong Fan, Chengguo Feng, Peng Li

“…To address the issue, a lightweight prior feature fusion network (LPFFNet) is proposed to better improve the performance of SAR ship detection. …”
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Machine Learning Models for Prognostic Assessment of Covid-19 Mortality Using Computed Tomography-Based Radiomics by Nima Yousefi, Maryam Salari, Vahid Ghavami, Saeed Akhlaghi

“…Methods: The U-net model was applied to automatically perform whole lung segmentations, extracting 107 texture, intensity, and morphological features. …”
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Deformable Feature Fusion and Accurate Anchors Prediction for Lightweight SAR Ship Detector Based on Dynamic Hierarchical Model Pruning by Yue Guo, Shiqi Chen, Ronghui Zhan, Wei Wang, Jun Zhang

“…To address these challenges, this article proposes a novel SAR ship detection network called DFES-Net, which incorporates deformable feature fusion and accurate anchor prediction to enhance detection performance. …”
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