Early feature study of Yunnan pine pinewood nematode disease based on hyperspectral remote sensing of ground objects by Xiao Zhang, Yingqun Gao, Lianjin Fu, Yiran Zhang, Zeyu Li, Qingtai Shu

“…Therefore, this study proposes a new approach for early detection of PWD using hyperspectral data combined with measured physiological parameters to obtain diagnostic spectra and optimal biochemical parameters for early detection. …”
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Introducing a Method for Backflow Detection in Lobe Blowers through Ultrasonic Technique by Ali Monazami, Somaye Mohammadi, Mehdi Behzad

“…Data analysis results show that the ultrasonic technique can detect the presence of backflow. …”
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Optimized Breast Cancer Classification Using PCA-LASSO Feature Selection and Ensemble Learning Strategies With Optuna Optimization by Prabhat Kumar Sahu, Taiyaba Fatma

“…The publicly available Breast Cancer Wisconsin (Diagnostic) dataset was utilized and underwent preprocessing steps, including dimensionality reduction and feature selection methods such as Principal Component Analysis (PCA) combined with Least Absolute Shrinkage and Selection Operator (LASSO). …”
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GeNIS: A modular dataset for network intrusion detection and classificationZenodo by Miguel Silva, Daniela Pinto, João Vitorino, José Gonçalves, Eva Maia, Isabel Praça

“…GeNIS follows a modular design, providing raw packet capture next generation (PCAPNG) files with over 37 million packets of each intermediate attack step to enable an in-depth analysis with different flow exporters, feature extraction, and feature selection tools, as well as filtered CSV files with over 2.8 million flows created with 5, 10, 30, and 60 s flow intervals. …”
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Novel Wavelet Convolutional Neural Networks for Signal Detection in OFDM-IM Systems by Yang Zhao, SI-YU Zhang, Yuexia Zhang, Gongpu Wang, Behnam Shahrrava

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Wind Turbine Fault Detection Through Autoencoder-Based Neural Network and FMSA by Welker Facchini Nogueira, Arthur Henrique de Andrade Melani, Gilberto Francisco Martha de Souza

“…The framework integrates autoencoder-based neural networks with Failure Mode and Symptoms Analysis, leveraging the strengths of both methodologies to enhance anomaly detection, feature selection, and fault localization. …”
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Beat-aligned motor synergies and kinematic beat detection in street dance movements by Keli Shen, Jun-ichiro Hirayama

“…Abstract Dance is a rich artistic expression that combines intricate human movements with music, emotion, and cultural elements. However, the analysis of complex dance movements poses significant challenges because of the lack of comprehensive motion capture data and efficient computational techniques for feature extraction. …”
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Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…The comprehensive analysis of the results reveals the highest accuracy of leukemia detection as compared to existing studies in the relevant literature.…”
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Automated Lightweight Model for Asthma Detection Using Respiratory and Cough Sound Signals by Shuting Xu, Ravinesh C. Deo, Oliver Faust, Prabal D. Barua, Jeffrey Soar, Rajendra Acharya

“…The successful implementation of a dual-sound analysis approach promises advancements in the early detection and management of asthma and COPD.We conclude that the proposed model holds strong potential to transform asthma diagnostic practices and support clinicians in their respiratory healthcare practices.…”
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Temporal Logical Attention Network for Log-Based Anomaly Detection in Distributed Systems by Yang Liu, Shaochen Ren, Xuran Wang, Mengjie Zhou

“…Detecting anomalies in distributed systems through log analysis remains challenging due to the complex temporal dependencies between log events, the diverse manifestation of system states, and the intricate causal relationships across distributed components. …”
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WSN intrusion detection method using improved spatiotemporal ResNet and GAN by Yang Jing

“…A network intrusion detection method that integrates improved spatiotemporal residual network and generative adversarial network (GAN) in a big data environment is proposed to address the issues of poor feature extraction and significant impact from data imbalance in most existing intrusion detection methods. …”
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Go Source Code Vulnerability Detection Method Based on Graph Neural Network by Lisha Yuan, Yong Fang, Qiang Zhang, Zhonglin Liu, Yijia Xu

“…With the widespread application of the Go language, the demand for vulnerability detection in Go programs is increasing. Existing detection models and methods have deficiencies in extracting source code features of Go programs and mainly focus on detecting concurrency vulnerabilities. …”
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Advancements in Hematologic Malignancy Detection: A Comprehensive Survey of Methodologies and Emerging Trends by Rajashree Nambiar, Ranjith Bhat, Balachandra Achar H V

“…This survey systematically examines the state-of-the-art in blood cancer detection through image-based analysis, aimed at identifying the most effective computational strategies and highlighting emerging trends. …”
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Wi-Pest:a method for detecting stored grain pests based on CSI by Shaowei SHAN, Weidong YANG, Le XIAO, Ke WANG

“…The environmental and biological factors that affect the food security during the food storage,such as the food temperature,environment humidity,moisture,gas,mildew,pests and others pose a threat to the food storage security,among which the pest is an important factor threatening food storage security.Therefore,a fast and effective detection method is needed to detect stored grain pests.Some of the existing methods are time consuming,using expensive equipment,potentially harmful to health and inefficient.A non-contact,fast and low-cost detection method for stored grain pests based on the amplitude of the channel state information (CSI) was proposed,namely,wireless-pest (Wi-Pest).The feasibility of the pest detection in the stored grain was verified by using CSI amplitude data.On this basis,a Wi-Pest detection method was designed.Firstly,the amplitude data of CSI was preprocessed by outliers removal,data normalization and noise elimination.Then the principal component analysis (PCA) was used to compress the data and extract the main feature components.Finally,random forest (RF) classification method was used to detect stored grain pests.Experiments show that the abnormal density of live pests in grain heaps can be detected under the line of sight (LOS) scenario,and the detection accuracy of the proposed method can reach 97% on average.…”
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A Review of Machine Learning Approaches for Non-Invasive Cognitive Impairment Detection by Muath Alsuhaibani, Ali Pourramezan Fard, Jian Sun, Farida Far Poor, Peter S. Pressman, Mohammad H. Mahoor

“…Facial analysis methods showed promise for visual modalities but were less extensively studied. …”
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Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques by Uwe Knauer, Sebastian Warnemünde, Patrick Menz, Bonito Thielert, Lauritz Klein, Katharina Holstein, Miriam Runne, Wolfgang Jarausch

“…Data processing consists of preprocessing for segmentation of the leaf area, feature extraction, classification and subsequent analysis of relevance of spectral bands. …”
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Tight sandstone fluid detection technology based on multi-wave seismic data by Yutan Dou, Daxing Wang, Mengbo Zhang, Fei Li, Guanghong Du, Yonggang Wang, Yuhua Zhao, Feng Liu, Yan Huang, Jie Zhang, Xiaojie Cui, Ligang Huang, Jun Zhu

“…Therefore, this study forms a series of seismic fluid detection technologies based on multi-wave seismic data, including the multi-wave “bright spot” feature analysis, multi-wave amplitude ratio technique, multi-wave amplitude versus offset analysis, multi-wave matched compression correlation analysis, and multi-wave pre-stack simultaneous inversion. …”
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Object detection with afordable robustness for UAV aerial imagery: model and providing method by Viacheslav Moskalenko, Artem Korobov, Yuriy Moskalenko

“…The model includes a transformer-based backbone, gate units, and simplified feature pyramid network with a RetinaNet detection head. …”
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Review of Surface-Defect Detection Methods for Industrial Products Based on Machine Vision by Quan Wang, Mengnan Wang, Jiadong Sun, Deji Chen, Pei Shi

“…It also offers a detailed analysis of recent developments and practical applications of large models in industry defect detection. …”
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Detection of Leaf Miner Infestation in Chickpea Plants Using Hyperspectral Imaging in Morocco by Mohamed Arame, Issam Meftah Kadmiri, Francois Bourzeix, Yahya Zennayi, Rachid Boulamtat, Abdelghani Chehbouni

“…This study addresses the problem of early detection of leaf miner infestations in chickpea crops, a significant agricultural challenge. …”
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