Genetic Algorithm-Based Weighted Constraint Target Band Selection for Hyperspectral Target Detection by Wenbin Chen, Xiyang Zhi, Jianming Hu, Lijian Yu, Qichao Han, Wei Zhang

“…To address this issue, this work proposes a novel band selection method, genetic algorithm-based weighted constraint target band selection (GA-WCTBS), which utilizes an improved genetic algorithm to optimize band subsets for small target detection. …”
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Research on high-resolution processing of frequency modulation combined signal for active sonar detection by Yaojun Jia, Pingbo Wang, Hongkai Wei, Qiang Chen, Yunhua Hu

“…Firstly, the ROC curve analysis shows that the detection performance of PAMP is significantly improved compared with PM and PP, and is close to the optimal detector. …”
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Hierarchical Feature Fusion and Enhanced Attention Mechanism for Robust GAN-Generated Image Detection by Weinan Zhang, Sanshuai Cui, Qi Zhang, Biwei Chen, Hui Zeng, Qi Zhong

“…These results show that the proposed method can not only achieve optimal performance on data with the same distribution, but also demonstrate strong generalization ability in cross-domain detection tasks.…”
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Causal analysis and impact of a systematic error detected about consumption associated with trastuzumab by Nuria Bujaldón Querejeta, Dolores Camacho Romera, José Antonio Pomares Pastor, María Sánchez Garnes, Mauricio Martínez Ramírez, Mercedes González Delgado

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Plastic Litter Detection in the Environment Using Hyperspectral Aerial Remote Sensing and Machine Learning by Marco Balsi, Monica Moroni, Soufyane Bouchelaghem

“…Plastic waste has become a critical environmental issue, necessitating effective methods for detection and monitoring. This article presents a machine-learning-based methodology and embedded solution to detect plastic waste in the environment using an airborne hyperspectral sensor operating in the short-wave infrared (SWIR) band. …”
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Reliable Event Detection via Multiple Edge Computing on Streaming Traffic Social Data by Yipeng Ji, Jingyi Wang, Yan Niu, Hongyuan Ma

“…We conduct experiments on social media text datasets describing various traffic events in cities such as Beijing and develop related social traffic event detection systems. The results indicate that our model can better implement streaming social traffic event detection, and is superior to most text classification methods.…”
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Unsupervised fake news detection on social media using hybrid Gaussian Mixture Model. by Sajida Perveen, Muhammad Shahbaz, Sami S Albouq, Khlood Shinan, Hanan E Alhazmi, Fatmah Alanazi, M Usman Ashraf, Rehan Ashraf

“…This research proposes an unsupervised approach using clustering algorithms, including Gaussian Mixture Model (GMM), K-means, and K-medoids, to eliminate the need for manual labeling in detecting fake news. In particular, it also proposes a novel hybrid method that leverages the Gaussian Mixture Model (GMM) in conjunction with the Group Counseling Optimizer (GCO), a metaheuristic optimization algorithm, to identify the optimal number of clusters for the detection of fake news. …”
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AccFIT-IDS: accuracy-based feature inclusion technique for intrusion detection system by C. Rajathi, P. Rukmani

“…One such mechanism is the Intrusion Detection System (IDS), which examines network traffic to identify and prevent attack. …”
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Non-Contact Detection of Wine Grape Load Volume in Hopper During Mechanical Harvesting by Haowei Liu, Xiu Wang, Jian Song, Mingzhou Chen, Cuiling Li, Changyuan Zhai

“…Issues of poor real-time performance and low accuracy in the detection of load volume in the hopper during the mechanized harvesting of wine grapes are addressed in this study through the development of a proposed volume detection method based on ultrasonic sensors. …”
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A Comparative Study of Customized Algorithms for Anomaly Detection in Industry-Specific Power Data by Minsung Jung, Hyeonseok Jang, Woohyeon Kwon, Jiyun Seo, Suna Park, Beomdo Park, Junseong Park, Donggeon Yu, Sangkeum Lee

“…This study compares and analyzes statistical, machine learning, and deep learning outlier-detection methods on real power-usage data from the metal, food, and chemical industries to propose the optimal model for improving energy-consumption efficiency. …”
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Epileptic Seizure Detection in EEG Signals Using Machine Learning and Deep Learning Techniques by Hepseeba Kode, Khaled Elleithy, Laiali Almazaydeh

“…This study focuses on classifying time-series data representation of EEG signals with machine learning-based classifiers by tuning parameters and deep learning-based One-Dimensional Convolutional Neural Network (1D CNN) methods. The primary objective is not only to determine the optimal classifier but also to emphasize critical metrics such as sensitivity, precision, and accuracy, which are critical in medical investigations, particularly for the early detection of diseases and patient care optimization. …”
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Forest Fire Detection Based on Enhanced Feature Information Capture and Long-Range Dependency by Wangke Lin, Jun Gao, Jingde Huang

“…However, in the early stages of a fire, the flames are typically small, and the smoke often bears a close resemblance to mist or fog, which makes prompt and accurate detection difficult and frequently causing the loss of the optimal response window. …”
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An adaptive neuro-fuzzy inference scheme for defect detection and classification of solar PV cells by Ranganai Tawanda Moyo, Mendon Dewa, Héctor Felipe Mateo Romero, Victor Alonso Gómez, Jose Ignacio Morales Aragonés, Luis Hernández-Callejo

“…Traditional defect detection and classification methods often face challenges in providing precise and adaptable solutions to this complex problem. …”
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Chemical Nose-Based Non-Invasive Detection of Breast Cancer Using Exhaled Breath by Yosef Matana, Shai Libson, Barak Amihood, Zvi Boger, David Lieberman, Offer Zeiri, Yehuda Zeiri

“…BC mortality is related to early tumor detection, highlighting the importance of early detection methods. …”
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An Efficient Approach Based on RAE-GAMI-NET for Long Range Attack Detection on Blockchain by Vasavi Chithanuru, Mangayarkarasi Ramaiah

“…The proposed explainable neural network model includes Residual Auto Encoder (RAE) guided generalized additive models with incorporating structured interactions (RAE-GAMI-Net) for LRA detection in PoS Blockchain In this work, a wrapper-based Binary Orchard Algorithm (W-BOA) is used to find the best features to lessen the dimensionality of extracted Characteristics, and a global feature extraction has been implemented based on multi-scale Densenet (MDensenet) that assures early convergence and optimal performance by providing global optimal solution. …”
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Quality control methods for Aedes albopictus sterile male production. by Fabrizio Balestrino, Arianna Puggioli, Marco Carrieri, Jérémy Bouyer, Romeo Bellini

“…These simple and cost-effective tools provide a valuable method to detect and amend potentially sub-standard procedures in the sterile male production line and hence contribute to maintaining optimal quality and field performance of the mosquitoes being released.…”
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Research on the Rapid Detection of Formaldehyde Emission From Wood-Based Panels Based on the AMSHKELM by Yinuo Wang, Huanqi Zheng, Hua Wang, Yucheng Zhou

“…To enable quick and accurate detection of formaldehyde emissions from wood-based panels and to address the complexities of the full-scale chamber method and the inaccuracy of sensor-based methods, a modified formaldehyde emission model based on AdaBoost-MSBKA-SVMD-HKELM (AMSHKELM) is proposed. …”
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Detection of intracranial hypertension in children using optical coherence tomography: a systematic review by Michael Hisaund, Sohaib R Rufai, Noor ul Owase Jeelani, Rebecca J McLean

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Rapid and Sensitive Detection of Thrombospondin-2 Using Nanoparticle Sensors for Cancer Screening and Prognosis by Maziyar Kalateh Mohammadi, Seyedsina Mirjalili, Md Ashif Ikbal, Hao Xie, Chao Wang

“…Thrombospondin-2 (THBS2) is a prevailing prognostic biomarker implicated in different cancer types, such as deadly colorectal, pancreas, and triple-negative breast cancers. While the current methods for cancer-relevant protein detection, such as enzyme-linked immunosorbent assay (ELISA), mass spectrometry, and immunohistochemistry, are feasible at advanced stages, they have shortcomings in sensitivity, specificity, and accessibility, particularly at low concentrations in complex biological fluids for early detection. …”
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RARELY DETECTED COMPLICATION DURING CATHETERIZATION OF INTERNAL JUGULAR VEIN — DAMAGE TO THE VAGUS NERVE by M. V. Bykov, V. V. Lazarev, K. S. Madorskii, V. G. Bagaev, L. V. Bykova

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