Structural Magnetic Resonance Imaging Brain Age Investigation in Athletes with Persistent Postconcussion Syndrome by Samuel Guay, Camille Charlebois-Plante, Sophie-Andrée Vinet, Marie-Eve Bourassa, Louis De Beaumont

“…Brain age prediction algorithms using structural magnetic resonance imaging (MRI) estimate the biological age of the brain by comparing it to a normal aging trajectory, allowing for the identification of deviations that may indicate slower or accelerated biological aging. …”
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Realistic synthetic dataset generation for cyber-physical systems: a performance evaluation by Yaa Acquaah, Kaushik Roy

“…The development and validation of models, algorithms, and control systems for CPS heavily relies on the availability of quality CPS datasets. …”
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Advances in optical biosensors as alternative diagnostics for clinical determination of ESKAPE bacteria by Maargavi Singh, Sreelakshmi C․S․, Chiranjay Mukhopadhyay, Sajan D. George, Pooja Nag, Kapil Sadani

“…In addition, incorporating artificial intelligence and machine learning algorithms in signal processing and feature extraction enhances biosensor performance and accelerates diagnostic accuracy. …”
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Leveraging machine learning for enhanced and interpretable risk prediction of venous thromboembolism in acute ischemic stroke care. by Youli Jiang, Ao Li, Zhihuan Li, Yanfeng Li, Rong Li, Qingshi Zhao, Guisu Li

“…Feature selection involved stepwise logistic regression and LASSO, with SHapley Additive exPlanations (SHAP) used to enhance model interpretability. …”
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Machine Learning Approaches for Real-Time Mineral Classification and Educational Applications by Paraskevas Tsangaratos, Ioanna Ilia, Nikolaos Spanoudakis, Georgios Karageorgiou, Maria Perraki

“…The main objective of the present study was to develop a real-time mineral classification system designed for multiple detection, which integrates classical computer vision techniques with advanced deep learning algorithms. …”
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Recent Facial Image Preprocessing Techniques: A Review by Rendra Soekarta, Ku Ruhana Ku-Mahamud

“…Facial image preprocessing is a critical step in various applications, including facial recognition, emotion detection, and biometric authentication. Preprocessing methods including normalization, noise reduction, illumination correction, alignment, resolution enhancement, data augmentation, and edge detection are essential for improving image quality and standardizing facial features in improving facial image quality. …”
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RF-Based Sensing and AI Decision Support for Stroke Patient Monitoring: A Digital Twin Approach by Sagheer Khan, Usman Anwar, Aftab Khan, Tughrul Arslan

“…Out of the 4 autonomous feature extraction methods, the Fine KNN algorithm with SAE structure 64-32-16-32-64 provided the highest accuracies of 88.2% and 74.8% for binary and multi-class classification.…”
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Depression and Anxiety Screening for Pregnant Women via Free Conversational Speech in Naturalistic Condition by Rafael T. Sousa, Gustavo D. M. Silva, Paula L. L. Pinto, Juliano Backes, Amanda S. Mota, Thiago M. Paixao, Maria G. S. Teixeira, Wilian H. Hisatugu, Anilton S. Garcia, Kelly S. Prado, Rodrigo S. Dias, Marco A. Galletta, Hermano Tavares

“…Machine learning algorithms were utilized combined with different audio feature sets to analyze these recordings in conjunction with PHQ-4 questionnaire scores. …”
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图像处理技术在齿轮缺陷检测中的应用 by 肖俊建, 王慧英

“…To deal with the defet of gear,the identification technology is studied.Applied with image forming、 edge detection、image transform、median filter、threshold segmentation、edge detection、 feature extraction、 pattern recognition,the method of threshold construction and the edge extraction algorithm are proposed.Lastly,the method of automatic identification technology of defects of gear is obtained.Advanced image processing technology is an effective method of controlling product quality and fault diagnosis.…”
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A Discriminative Target Equation-Based Face Recognition Method for Teaching Attendance by Feng Xu, Haiwei Wang

“…For the face recognition process, the system uses the Ad boost algorithm based on Hear features to achieve face detection, preprocesses the face samples with gray normalization, rotation correction, and size correction, and uses the method based on LBP features to achieve face recognition. …”
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Comprehensive Multi-indicator Prediction Model for Storage Quality of Multi-cultivar Kiwifruit Based on Visible-Near Infrared Spectroscopy by Zizhao LIANG, Xin LI, Pu LIU, Wenqiang GUAN, Ming LI

“…After the use of different preprocessing algorithms, such as first-order derivatives (FD), standard normal variate (SNV), second-order derivatives, convolutional smoothing, and FD+SNV, the data were combined with competitive adaptive reweighted sampling (CARS) for feature wavelength selection. …”
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Attention-enhanced StrongSORT for robust vehicle tracking in complex environments by Wei Xu, Xiaodong Du, Ruochen Li, Bingjie Li, Yuhu Jiao, Lei Xing

“…Abstract While multi-object tracking is critical for autonomous driving systems, traditional algorithms exhibit three fundamental limitations in complex scenarios: (1) blurred feature representation under occlusion and re-identification scenarios causing identity switches, (2) insufficient sensitivity to scale-variant targets due to fixed geometric constraints in conventional IoU-based loss functions, and (3) gradient degradation in deep convolutional layers hindering discriminative feature learning. …”
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Efficient Brain Tumor Segmentation for MRI Images Using YOLO-BT by Mengying Xiong, Aiping Wu, Yue Yang, Qingqing Fu

“…It can be seen that the YOLO-BT algorithm is suitable for brain tumor detection and segmentation.…”
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Defect intelligent recognition of membrane product based on deep learning by Maonian Wu, Ling Li, Wei Peng, Tao Wu, Jinwei Yu, Bo Zheng, Shaojun Zhu

“…In empirical experiments, we employ the YOLOv7 architecture as the foundation framework, integrating the proposed methodologies for the purpose of detecting defects in the membrane. The empirical evidence demonstrates a notable improvement in the performance of detecting defects in membrane products using the SE-CAR feature enhancement module and Distance-IoU Non-Maximum Suppression algorithm. …”
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A non-invasive diagnostic approach for neuroblastoma utilizing preoperative enhanced computed tomography and deep learning techniques by Yuanyuan Wang, Fangfang Wang, Zixin Qin, Yongcheng Fu, Jingyue Wang, Shangkun Li, Da Zhang

“…In light of the image features, we have implemented the inverse residual-based attention structure (iRMB) within the detection network of YOLOv8, thereby enhancing the model’s ability to focus on significant features present in the images. …”
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A Combined Deep CNN: LSTM with a Random Forest Approach for Breast Cancer Diagnosis by Almas Begum, V. Dhilip Kumar, Junaid Asghar, D. Hemalatha, G. Arulkumaran

“…The main objective of this paper is to propose a deep learning technique in combination with a convolution neural network (CNN) and long short-term memory (LSTM) with a random forest algorithm to diagnose breast cancer. Here, CNN is used for feature extraction, and LSTM is used for extracted feature detection. …”
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Artificial Intelligence Performance in Cardiac Magnetic Resonance Strain Analysis for Aortic Stenosis: Validation with Echocardiography and Healthy Controls by Žygimantas Abramikas, Ieva Jasiukevičiūtė, Giedrė Balčiūnaitė, Sigita Glaveckaitė, Darius Palionis, Nomeda Valevičienė

“…However, the higher error rates in AS patients compared to controls underscore the need for more advanced AI algorithms to improve performance in cardiac pathology.…”
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Automated diagnosis of respiratory diseases from lung ultrasound videos ensuring XAI: an innovative hybrid model approach by Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan, Asif Karim, Sami Azam, Nur Mohammad Fahad, Niusha Shafiabady, Kheng Cher Yeo, Friso De Boer

“…The DSS, incorporating Layer Class Activation Mapping (LayerCAM) and heatmaps, improved interpretability and reliability, and PDF graphs facilitated precise decision-making by identifying feature boundaries. The DSS facilitates clinical marker analysis, and the validation by using the proposed algorithms highlights its impact on a reliable diagnosis outcome.DiscussionOur proposed methodology could assist radiologists in accurately detecting and comprehending the patterns of respiratory disorders.…”
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Robust Extrinsic Calibration for LiDAR-Camera Systems via Depth and Height Complementary Supervision Network by Chen Yaqing, Wang Huaming

“…Additionally, we introduce an Attention-based Fusion Module (AFM) for efficient feature fusion. Furthermore, we incorporate time compensation and iterative calibration techniques to further enhance the robustness of the algorithm in handling initial alignment errors. …”
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Monitoring Pine Wilt Disease Using High-Resolution Satellite Remote Sensing at the Single-Tree Scale with Integrated Self-Attention by Wenhao Lv, Junhao Zhao, Jixia Huang

“…This study introduces several advanced self-attention algorithms into the task of satellite-based monitoring of pine wilt disease to enhance detection performance. …”
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