Classifying active and inactive states of growing rabbits from accelerometer data using machine learning algorithms by Mónica Mora, Lucile Riaboff, Ingrid David, Juan Pablo Sánchez, Miriam Piles

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CONSTRUCTING A MATHEMATICAL MODEL FOR ONE-DIMENSIONAL DIFFERENTIAL CORRELATOR by Vladimir P. Gerasimov, Alexander Yu. Darzhanya, Vladimir D. Kovalev

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Diagnosis and Classification of Two Common Potato Leaf Diseases (Early Blight and Late Blight) Using Image Processing and Machine Learning by H. Koroshi Talab, D. Mohammad Zamani, M. Gholami Parashkoohi

“…The most effective features for disease detection were identified using a combination of all three feature sets. …”
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Mopidip: a modular real-time pipeline for machinery diagnosis and prognosis based on deep learning algorithms by Mattia Pujatti, Davide Calzà, Andrea Gobbi, Piergiorgio Svaizer, Marco Cristoforetti

“…The tool integrates the data acquisition and processing steps with a configurable feature extraction phase. Moreover, the system also integrates deep learning algorithms for diagnosis and prognosis, including a domain adaptation stage to permit transfer learning and increase generalizability. …”
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Classification Prediction of Jujube Variety Based on Hyperspectral Imaging: A Comparative Study of Intelligent Optimization Algorithms by Quancheng Liu, Jun Zhou, Zhaoyi Wu, Didi Ma, Yuxuan Ma, Shuxiang Fan, Lei Yan

“…The data were then processed using Baseline correction, Multiplicative Scatter Correction (MSC), and Savitzky-Golay first derivative (SG1st) spectral preprocessing techniques, followed by feature enhancement with the Competitive Adaptive Reweighted Sampling (CARS) algorithm. …”
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GA-PE-VMD and MSE Methods for Milling Chatter Feature Extraction of Thin-walled Parts by WANG Hanbin, LI Maoyue, LIU Xianli, WANG Zhixue, MENG Boyang

“…Chatter leads to poor surface quality, dimensional error and reducing the service life of tools and machines.Therefore, a reliable detection method is needed to identify chatter.Aiming at the problem of chatter detection in the milling process of thin-walled structures, a chatter feature extraction method of thin-walled parts based on optimal variational mode decomposition and multi-scale sample entropy is proposed.Firstly, in order to solve the problem of parameter selection in variational modal decomposition, a parameter adaptive method based on genetic algorithm optimization and minimum permutation entropy is proposed. …”
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Detection Model for 5G Core PFCP DDoS Attacks Based on Sin-Cos-bIAVOA by Zheng Ma, Rui Zhang, Lang Gao

“…A 5G core network DDoS attack detection model is been proposed which utilizes a binary improved non-Bald Eagle optimization algorithm (Sin-Cos-bIAVOA) originally designed for IoT DDoS detection to select effective features for DDoS attacks. …”
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Advanced Human Pose Estimation and Event Classification Using Context-Aware Features and XGBoost Classifier by Wasim Wahid, Aisha Ahmed AlArfaj, Ebtisam Abdullah Alabdulqader, Touseef Sadiq, Hameedur Rahman, Ahmad Jalal

“…Keypoint detection is achieved through pose estimation, and full-body feature extraction includes using OpenPose for movable body parts, the Lucas-Kanade method for a 3D Cartesian view, and Texton Map techniques. …”
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Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local Features by Xiaorong Zhang, Siyuan Li, Zhongyang Xing, Binliang Hu, Xi Zheng

“…The high-resolution spatial features are first employed for detecting scale-invariant features, while the spectral information is used for matching, and then the idea of image stitching is employed to fuse the image after fine registration to obtain high-precision registration results. …”
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A Novel Machine Learning Technique for Fault Detection of Pressure Sensor by Xiufang Zhou, Aidong Xu, Bingjun Yan, Mingxu Gang, Maowei Jiang, Ruiqi Li, Yue Sun, Zixuan Tang

“…Subsequently, via the sliding window algorithm, both the time-domain features and frequency-domain features of the trend components are extracted, and finally, the XGBoost algorithm is used to detect faults. …”
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A twin CNN-based framework for optimized rice leaf disease classification with feature fusion by Prameetha Pai, S. Amutha, Mustafa Basthikodi, B. M. Ahamed Shafeeq, K. M. Chaitra, Ananth Prabhu Gurpur

“…The framework integrates an optimized feature fusion algorithm using pre-trained CNN models to improve disease detection accuracy. …”
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The Ground-Penetrating Radar Image Matching Method Based on Central Dense Structure Context Features by Jie Xu, Qifeng Lai, Dongyan Wei, Xinchun Ji, Ge Shen, Hong Yuan

“…However, GPR images, due to their low resolution, cannot extract well-defined geometric features such as corners and lines. Thus, traditional visual image processing algorithms perform inadequately when applied to GPR image matching. …”
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Research on Feature Extraction Method and Process Optimization of Rolling Bearing Faults Based on Electrostatic Monitoring by Ruochen Liu, Han Yin, Jianzhong Sun, Lanchun Zhang

“…The method maintains fast convergence while analysing the extraction effect by comparing the measured signals of rolling bearing outer ring and bearing roller faults with the traditional StOMP algorithm, and the results show that the CcStOMP algorithm has obvious advantages in accurately extracting the fault features in the electrostatic monitoring signals of rolling bearings.…”
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Ensemble-RNN: A Robust Framework for DDoS Detection in Cloud Environment by Asha Varma Songa, Ganesh Redy Karri

“…This paper proposes an intrusion detection framework using Ensemble feature selection with RNN (ERNN) to tackle the problem at hand. …”
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Optimizing Bi-LSTM networks for improved lung cancer detection accuracy. by Su Diao, Yajie Wan, Danyi Huang, Shijia Huang, Touseef Sadiq, Mohammad Shahbaz Khan, Lal Hussain, Badr S Alkahtani, Tehseen Mazhar

“…We employed traditional hand-crafted features, such as Gray Level Co-occurrence Matrix (GLCM) features, in conjunction with traditional machine learning algorithms. …”
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Aerial Biological Target Classification Based on Time–Frequency Multi-Scale Feature Fusion Network by Lianjun Wang, Rui Wang, Weidong Li, Jiangtao Wang, Yujia Yan, Cheng Hu

“…The analysis revealed that radar cross section (RCS) features are insufficient to support insect and bird classification tasks, as aerial biological targets may be detected in radar sidelobes, leading to uncertainty in RCS values. …”
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A Multimodal Image Registration Method for UAV Visual Navigation Based on Feature Fusion and Transformers by Ruofei He, Shuangxing Long, Wei Sun, Hongjuan Liu

“…This paper proposes a CNN-Transformer hybrid network model for feature detection and feature matching. ResNet50 is used as the backbone network for feature extraction. …”
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A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition by Hanying Guo, Siying Chen, Yongjiang Zhou, Ting Xu, Yuhao Zhang, Hongliang Ding

“…To minimize redundant information, we propose an improved Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm for selecting the optimal feature subset, ensuring both the efficiency and accuracy of fatigue recognition. …”
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Detect Flame Fire Using Fractal Geometry in Color Digital Images by Laheeb Ibrahim, Khalil Alsaif, Hasan Alnima

“…In this research an algorithm for detecting fire flame in the colored digital images is built. …”
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Multi-Scale Spatiotemporal Feature Enhancement and Recursive Motion Compensation for Satellite Video Geographic Registration by Yu Geng, Jingguo Lv, Shuwei Huang, Boyu Wang

“…Based on the SuperGlue matching algorithm, the method achieves automatic matching of inter-frame image points by introducing the multi-scale dilated attention (MSDA) to enhance the feature extraction and adopting a joint multi-frame optimization strategy (MFMO), designing a recursive motion compensation model (RMCM) to eliminate the cumulative effect of the orbit error and improve the accuracy of the inter-frame image point matching, and using a rational function model to establish the geometrical mapping between the video and the ground points to realize the georeferencing of satellite video. …”
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