Hyperspectral imaging combined with residual-attention-net for spectral-spatial feature fusion in liver disease diagnosis by Yunze Li, Jingjing Wang, Miaoqing Zhao, Jinlin Deng, Chongxuan Tian, Qize Lv, Yifei Liu, Kun Ru, Wei Li

“…Sensitivity and specificity values also indicated strong diagnostic performance. The key innovation of this study lies in the development of the 3D Ra-Net model and the efficient extraction of joint spatial-spectral features. …”
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MFCEN: A lightweight multi-scale feature cooperative enhancement network for single-image super-resolution by Jiange Liu, Yu Chen, Xin Dai, Li Cao, Qingwu Li

“…Experiments demonstrated that the proposed model surpasses the reconstruction performance of the 498K-parameter SPAN model with a mere 488K parameters. …”
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Machine learning for predicting neoadjuvant chemotherapy effectiveness using ultrasound radiomics features and routine clinical data of patients with breast cancer by Pu Zhou, Pu Zhou, Hongyan Qian, Pengfei Zhu, Jiangyuan Ben, Jiangyuan Ben, Guifang Chen, Qiuyi Chen, Lingli Chen, Jia Chen, Ying He, Ying He

“…Combining the Rad score with clinical features in the GBM model resulted in superior predictive performance (AUC of 0.939 and an accuracy of 0.87). …”
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DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…In response to the limitations of current infrared and visible light image fusion algorithms-namely insufficient feature extraction, loss of detailed texture information, underutilization of differential and shared information, and the high number of model parameters-this paper proposes a novel multi-scale infrared and visible image fusion method with two-branch feature interaction. …”
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Feature selection using a multi-strategy improved parrot optimization algorithm in software defect prediction by Qi Fei, Guisheng Yin, Zhian Sun

“…Secondly, to mitigate the adverse impact of irrelevant features on model performance in traditional software defect prediction methods, this study introduces a binary multi-strategy enhanced Parrot Optimization algorithm (BMEPO) for optimizing feature selection. …”
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Improving Gaussian Naive Bayes classification on imbalanced data through coordinate-based minority feature mining by Wei Wang, Li Yan, Fen Liu, Yanxi Li

“…As a widely used classification model, the Gaussian Naive Bayes (GNB) classifier experiences a significant decline in performance when handling imbalanced data. …”
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Exploring a role for performance management in residential child care by Russell Sutherland

“…This paper seeks to explore the features of performance management and will evaluate Best Value and the National Standards as frameworks on which to base performance management. …”

Integrated multi-task feature learning and interactive active optimization for scene retargeting in preschool educational applications by Suhui Yao, Lan Lv

“…These GSPs are further transformed into hierarchical deep features using a multi-layer representation, followed by refinement through a Gaussian mixture model (GMM) to enhance scene understanding and retargeting fidelity. …”
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Enhancing automatic electric vehicle charging: a deep learning approach with YOLO and feature extraction techniques by Phasuwut Chunnapiya, Porawat Visutsak

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The topology of molecular representations and its influence on machine learning performance by Florian Rottach, Sebastian Schieferdecker, Carsten Eickhoff

“…In this work, we present TopoLearn, a model that predicts the effectiveness of representations on datasets based on the topological characteristics of the corresponding feature space. …”
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Multi-Biometric Feature Extraction from Multiple Pose Estimation Algorithms for Cross-View Gait Recognition by Ausrukona Ray, Md. Zasim Uddin, Kamrul Hasan, Zinat Rahman Melody, Prodip Kumar Sarker, Md Atiqur Rahman Ahad

“…This paper aims to bridge this performance gap by introducing a multi-biometric framework that extracts features from multiple HPE algorithms for gait recognition, employing feature-level fusion (FLF) and decision-level fusion (DLF) by leveraging a single-source multi-sample technique. …”
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AI and corporeal knowledge: inventing and performing with prostheses and sonic organs by Marco Donnarumma, Marco Donnarumma

“…The mainstream development of AI for artistic expression thrives on predictive models that are supposedly capable of abstracting creative ideas and actions into computable features. …”
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Comparison of performance of cervical cancer grading based on acetowhite areas by Won Jin Yang, So Hyeon Lee, Young Jae Kim, Kwang Gi Kim

“…Using four classifiers (Logistic Regression(LR), Random Forest(RF), XGBoost(XGB), and Support Vector Machine(SVM)), 464 cervical images (228 atypical and 236 positive cases) were analyzed. From a set of 75 features, the classifiers identified the top 5 based on feature importance. …”
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Point rotation invariant features and attention fusion network for point cloud registration of 3D shapes by Zeyang Liu, Zhiguo Lu, Yancong Shan

“…Leveraging the strengths of the PointNet+ + structure and attention mechanism, a fresh feature extraction module for point clouds is devised, ensuring efficient feature extraction and matching. …”
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Multi-featured spatial-temporal and dynamic multi-graph convolutional network for metro passenger flow prediction by Chuan Zhao, Xin Li, Zezhi Shao, HongJi Yang, Fei Wang

“…To address these challenges, we developed a novel model called the multi-featured spatial-temporal (MFST) and dynamic multi-graph convolutional network (DMGCN) model. …”
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Power Line Segmentation Algorithm Based on Lightweight Network and Residue-like Cross-Layer Feature Fusion by Wenqiang Zhu, Huarong Ding, Gujing Han, Wei Wang, Minlong Li, Liang Qin

“…To address the challenges of small target scale, complex backgrounds, and excessive model parameters in existing deep learning-based power line segmentation algorithms, this paper introduces RGS-UNet, a lightweight segmentation model integrating a residual-like cross-layer feature fusion module. …”
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Integrating multimodal imaging and peritumoral features for enhanced prostate cancer diagnosis: A machine learning approach. by Huadi Zhou, Mei Xie, Hemiao Shi, Chenhan Shou, Meng Tang, Yue Zhang, Yue Hu, Xiao Liu

“…<h4>Results</h4>The model incorporating multimodal imaging features and peritumoral characteristics showed superior classification performance. …”
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Image small target detection in complex traffic scenes based on Yolov8 multiscale feature fusion by Xuguang Chai, Meizhi Zhao, Jing Li, Junwu Li

“…Additionally, employing a feature distillation technique permits the student model to absorb crucial feature representations from the teacher model, circumventing the detrimental effects of semantic disparities across stages. …”
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IoT-enhanced multi-attention and lightweight feature integration for human pose estimation in motion training systems by Junwen Chen, Jian Yang, Zhiqun Wang

“…IoT-based motion sensors are integrated with vision-based keypoint detection to enhance pose estimation accuracy, particularly in occluded or high-speed movement scenarios. The model employs the LSFE stacked feature extraction module to enhance multi-scale feature adaptability, incorporates the LFAM local attention mechanism (SPAM + CARM) to improve key joint modeling, and introduces the GEAM global enhancement module to ensure keypoint stability and consistency. …”
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Extracting of Fault Features for Rotating Machinery of High-speed Train Based on EEMD Energy Entropy-LPP by Chen ZHANG, Tao FANG, Kaiqi YAN

“…By comparing the classification effects of the first feature extraction and the second feature extraction, the results show that the model had superior clustering performance and could accurately identify several common high-speed train rotor system failure types.…”
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