Presenting a Text Mining Algorithm to Identify Emotion in Persian Corpus by Masoud Garshasbi, Anahid Rais-Rohani, Mohammadreza Kabaranzadeh Ghadim

“…In the first approach, the algorithm is capable of detecting only one emotional word in a sentence, and then it improves to detect boosters and negating and stop word list as well. …”
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Identifying Irregular Potatoes by Developing an Intelligent Algorithm Based on Image Processing by Afshin Azızı, Yousef Abbaspour-gılandeh

“…The objective of this study was to develop an algorithm based on image processing for detecting misshapen potatoes from the mass of potatoes and obtaining homogeneous products. …”
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A Space-Time Plume Algorithm to Represent and Compute Dynamic Places by Brent Dell, May Yuan

“…Building on this, we developed Space-Time Plume, a new algorithm for detecting and tracking evolving event clusters as smoke plumes in space and time, representing dynamic places. …”
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Effects of data transformation and model selection on feature importance in microbiome classification data by Zuzanna Karwowska, Oliver Aasmets, Estonian Biobank research team, Tomasz Kosciolek, Elin Org

“…However, while different transformations resulted in comparable classification performance, the most important features varied significantly, which highlights the need to reevaluate machine learning–based biomarker detection. …”
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Image Processing Using Feature-Based Segmentation Techniques for the Analysis of Medical Images by Christodoss Prasanna Ranjith, Krishnamoorthy Natarajan, Sindhu Madhuri, Mahesh Thylore Ramakrishna, Chandrasekhar Rohith Bhat, Vinoth Kumar Venkatesan

“…Unlike classic K-means, which requires you to choose the number of clusters before executing the algorithm, adaptive K-means identifies the best number of clusters based on the features of the data. …”
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Precision Marketing Method of E-Commerce Platform Based on Clustering Algorithm by Bei Zhang, Luquan Wang, Yuanyuan Li

“…In addition, based on the idea of the K-mode clustering algorithm, this paper proposes a clustering method combining related rules with multivalued discrete features (MDF). …”
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A Deep Learning Method for Automatic Coronal Mass Ejection Feature Identification by P. Yang, H. S. Fu, J. B. Cao, F. Shen

“…As space activities become increasingly frequent and infrastructure more reliant on space-based systems, the rapid and accurate detection and tracking of CMEs is critical. Here, we present a deep learning–based algorithm for automated CME feature extraction, comprising four key stages: image preprocessing, segmentation, tracking, and feature extraction. …”
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Photovoltaic module dataset for automated fault detection and analysis in large photovoltaic systems using photovoltaic module fault detectionMendeley Data by Rotimi-Williams Bello, Pius A. Owolawi, Etienne A. van Wyk, Chunling Du

“…Because the data comes from a single-day collection and one week laboratory experiment, it makes the data more suitable for testing algorithms designed for fault detection. The dataset is publicly and freely available to the scientific community at 10.17632/5ssmfpgrpc.1…”
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UAV-to-Ground Target Detection Based on YOLO-DSBE by Meng Pengshuai, Wang Feng, Zhai Weiguang, Ma Xingyu, Zhao Wei

“…To address the issues of complex background, small target scale, mutual occlusion and high missed detection rate in UAV captured images, this paper proposes a ground target detection algorithm based on YOLO-DSBE.The DC-ELAN and DC-MP modules based on deformable convolution are proposed to adapt to input features of different shapes and sizes, and to improve the network’s ability to parse features in complex backgrounds; A high-resolution multi-scale detection layer is designed to boost the algorithm’s capability in extracting small target features, thereby improving the detection accuracy of minute targets. …”
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Bridge Deformation Monitoring Combining 3D Laser Scanning with Multi-Scale Algorithms by Dongmei Tan, Wenjie Li, Yu Tao, Baifeng Ji

“…To address the inefficiencies and limited spatial resolution of traditional single-point monitoring techniques, this study proposes a multi-scale analysis method that integrates the Multi-Scale Model-to-Model Cloud Comparison (M3C2) algorithm with least-squares plane fitting. This approach employs the M3C2 algorithm for qualitative full-field deformation detection and utilizes least-squares plane fitting for quantitative feature extraction. …”
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Synergistic use of handcrafted and deep learning features for tomato leaf disease classification by Mohamed Bouni, Badr Hssina, Khadija Douzi, Samira Douzi

“…Abstract This research introduces a Computer-Aided Diagnosis-system designed aimed at automated detections & classification of tomato leaf diseases, combining traditional handcrafted features with advanced deep learning techniques. …”
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Using Electrocardiogram Signal Features and Heart Rate Variability to Predict Epileptic Attacks by Ying Jiang, Yuan Feng, Danni Lu, Lin Yang, Qun Zhang, Haiyan Yang, Ning Li

“…We used a multivariate statistical process control algorithm for abnormality detection. The presented algorithm was evaluated on a dataset consisting of 17 patients, where the obtained results show that the proposed method can predict epileptic attacks with an accuracy of 88.2%. …”
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SLPOD: superclass learning on point cloud object detection by Xiaokang Yang, Kai Zhang, Yangyue Feng, Beibei Su, Yiming Cai, Kaibo Zhang, Zhiheng Zhang

“…To tackle this challenge, we introduce SLPOD, a Superclass-based point cloud object detection algorithm. Employing a siamese network structure, SLPOD conducts unsupervised clustering of samples within the same category to enhance the extraction of individual-specific features, thereby improving detection accuracy when confronted with complex datasets. …”
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Predictive modeling for rework detection in sustainable building projects by AbdulLateef Olanrewaju, Kafayat Shobowale

“…The dataset consisted of 75 responses, with 17 rework predictors. Feature scaling and normalisation were performed across the dataset to standardise the features. …”
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AC-YOLO: citrus detection in the natural environment of orchards by Xu Xiao, Yaonan Wang, Yiming Jiang, Haotian Wu, Zhe Zhang, Rujing Wang

“…Firstly, in the Resblock module of the YOLOv4 backbone feature extraction network, the AC network structure is integrated with different levels of feature mapping to fuse context information as small targets. …”
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Neurophysiological Approaches to Lie Detection: A Systematic Review by Bewar Neamat Taha, Muhammet Baykara, Talha Burak Alakuş

“…The goal is to summarize commonly used EEG signal processing techniques, feature extraction methods, and classification algorithms, identifying those that yield the highest accuracy in lie detection tasks. …”
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Independently Identifying Noise Clusters in 2D LiDAR Scanning with Clustering Algorithms by Chiew Wei Wen, Chuan Hsian Pu

“…LiDAR environmental mapping technology is often highly praised for its precise mapping information with intricate features for various detection or tracking based applications. …”
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Heart Disease Prediction Using Ensemble Tree Algorithms: A Supervised Learning Perspective by Enoch Sakyi-Yeboah, Edmund Fosu Agyemang, Vincent Agbenyeavu, Akua Osei-Nkwantabisa, Priscilla Kissi-Appiah, Lateef Moshood, Lawrence Agbota, Ezekiel N. N. Nortey

“…These metrics indicate a superior ability to distinguish between patients with and without heart disease, effectively making it particularly valuable for clinical applications where early detection can save lives. The SHapley Additive exPlanations (SHAP) framework adopted to investigate the relative importance of the features in predicting heart disease revealed the most influential predictors (ST slope, chest pain type, old peak, and cholesterol), further aiding the understanding of heart disease mechanisms. …”
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A spike is a spike: On the universality of spike features in four epilepsy models by Armen Sargsyan, Pablo M. Casillas‐Espinosa, Dmitri Melkonian, Terence J. O'Brien, Gilles vanLuijtelaar

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DTFA-Net: Dynamic and Texture Features Fusion Attention Network for Face Antispoofing by Xin Cheng, Hongfei Wang, Jingmei Zhou, Hui Chang, Xiangmo Zhao, Yilin Jia

“…We proposed a dynamic information fusion structure of an interchannel attention block to fuse the magnitude and direction of optical flow to extract facial motion features. In addition, for the face detection failure of HOG algorithm under complex illumination, we proposed an improved Gamma image preprocessing algorithm, which effectively improved the face detection ability. …”
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