Text Detection Method With Emphasis on Text Component Importance and Lightweight Design by Lanlan Yin, Qiming Wu

“…Therefore, this study proposes an image scene text detection method based on a lightweight deep relation inference scene text detection algorithm. …”
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Evaluation of the operational MODIS cloud mask product for detecting cirrus clouds by Ż. Nguyen Huu, Ż. Nguyen Huu, Ż. Nguyen Huu, A. Z. Kotarba, A. Wypych

“…</p> <p>Using CALIOP data as the reference, we evaluated six tests for cirrus and high cloud detection considered in the MODIS cloud masking algorithm and their combination (all tests consolidation, ATC). …”
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Application of Naive Bayes Algorithm for Analysis of User Reviews on Mobile Legends Game: Bang Bang by Al-Muchlis Syachrul Ramadani Roba, Siti Lailiyah, Amelia Yusnita

“…This study conducts sentiment analysis on user reviews using three variants of the Naïve Bayes algorithm: BernoulliNB, GaussianNB, and MultinomialNB. …”
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Molecular detection of Bartonella spp. and Rickettsia spp. in bat ectoparasites in Brazil. by Renan Bressianini do Amaral, Elizabete Captivo Lourenço, Kátia Maria Famadas, Amanda Barbosa Garcia, Rosangela Zacarias Machado, Marcos Rogério André

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BiFormer for Scene Graph Generation Based on VisionNet With Taylor Hiking Optimization Algorithm by S. Monesh, N. C. Senthilkumar

“…The superiority of VisionNet is increased by training the hyperparameters using the Taylor hiking optimization algorithm (THOA). Furthermore, extensive experimental results were obtained using VisionNet_THOA, where VisionNet_THOA attained an accuracy of 94.867%, a True Negative Rate (TNR) of 93.877%, and a True Positive Rate (TPR) of 96.654%, a Precision of 91.765%, and F-Measure of 94.146%.…”
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Evaluation and Early Detection of Downy Mildew of Lettuce Using Hyperspectral Imagery by Songtao Ban, Minglu Tian, Dong Hu, Mengyuan Xu, Tao Yuan, Xiuguo Zheng, Linyi Li, Shiwei Wei

“…This study combines hyperspectral imaging technology with biochemical parameter analysis to facilitate the disease severity evaluation and early detection of lettuce downy mildew. The results reveal a significant negative correlation between the disease index (DI) and the levels of flavonoids (<i>r</i> = −0.523) and anthocyanins (<i>r</i> = −0.746), indicating the role of these secondary metabolites in enhancing plant resistance. …”
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Detection and Geolocation of Peat Fires Using Thermal Infrared Cameras on Drones by Temitope Sam-Odusina, Petrisly Perkasa, Carl Chalmers, Paul Fergus, Steven N. Longmore, Serge A. Wich

“…Finally, a geolocation algorithm is presented to identify the GNSS location of these fires once they are detected in an image to aid fire-fighting responses. …”
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Case-Based Approach to Detect Cancer in Women with Curative Intent at Beginning by Imran Majeed, Ahmad Imran, Mazhar Hussain, Mubahir Ali Syed, Tuba Zainab, Hamza Waheed, Tayyaba Dawood, Iqra Danish, Maryam Zeb, Kashif Hameed, Mehreen Farooq, Fatima Amjad, Razia Faqeer, Maria Abdullah

“…The outcomes acquired by CBR are compared with multiple Knowledge-based algorithms. Conclusion: The CBR-based approach delivered improved results when contrasted with the wide range of various strategies regarding precision, recall, misleading negative rate, genuine positive rate and F-measure for dangerous cases.…”
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Impact of Machine Learning on Intrusion Detection Systems for the Protection of Critical Infrastructure by Avinash Kumar, Jairo A. Gutierrez

“…This paper investigates the efficacy of various machine learning algorithms for anomaly detection within critical infrastructure, using the Secure Water Treatment (SWaT) dataset, a comprehensive collection of time-series data from a water treatment testbed, to experiment upon and analyze the findings. …”
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Integrating Information Gain and Chi-Square for Enhanced Malware Detection Performance by Fauzi Adi Rafrastara, Wildanil Ghozi, Ramadhan Rakhmat Sani, Lekso Budi Handoko, Abdussalam Abdussalam, Elkaf Rahmawan Pramudya, Faizal M. Abdollah

“…Recent studies have shown that this challenge can be addressed by employing machine learning algorithms for detection. Some studies have also implemented various feature selection methods to optimize detection efficiency. …”
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PCR-detection rates of T. pallidum ssp. pallidum in swab samples from the Czech Republic (2004–2022): Combined RPR, IgM, and PCR tests efficiently detect active syphilis by Eliška Vrbová, Petra Pospíšilová, Eliška Dastychová, Martina Kojanová, Miluše Kreidlová, Daniela Vaňousová, Filip Rob, Přemysl Procházka, Alena Krchňáková, Vladimír Vašků, Radim Strnadel, Olga Faustmannová, Monika Dvořáková Heroldová, Ivana Kuklová, Hana Zákoucká, David Šmajs

“…Our findings show that the reverse algorithm for detecting syphilis could be substantially improved by adding IgM and PCR testing.…”
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Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders by HU Tianzhu, SHEN Yulong, REN Baoquan, HE Ji, LIU Chengliang, LI Hongjun

“…The hierarchical clustering algorithm was used to divide the composite statistical features, and the separated features were input to multiple small memory-enhanced autoencoders in the integrated architecture for independent training, which reduced the computational complexity and solved the problem of false negatives caused by the overfitting of the reconstruction effect of the traditional autoencoder. …”
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Anomaly Detection in Wireless Sensor Networks Using Immune-Based Bioinspired Mechanism by Ramsha Rizwan, Farrukh Aslam Khan, Haider Abbas, Sajjad Hussain Chauhdary

“…In this paper, we propose a bioinspired solution using Negative Selection Algorithm (NSA) of the AIS for anomalies detection in WSNs. …”
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Automated concrete exposed reinforcement and corrosion detection and measurement using coloured illumination by Dow Hamish, Darby Andrew, Perry Marcus, Zhang Feng

“…Additionally, the algorithm’s corrosion surface area measurements produced a maximum relative error of negative 8 %. …”
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Deep learning detects retropharyngeal edema on MRI in patients with acute neck infections by Oona Rainio, Heidi Huhtanen, Jari-Pekka Vierula, Janne Nurminen, Jaakko Heikkinen, Mikko Nyman, Riku Klén, Jussi Hirvonen

“…This study aimed to develop a deep learning-based algorithm for the automated detection of RPE. Methods We developed a deep neural network consisting of two parts using axial T2-weighted water-only Dixon MRI images from 479 patients with acute neck infections annotated by radiologists at both slice and patient levels. …”
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Severity Classification of Freezing of Gait Using Machine-Learning Algorithms: A Hidden State Model Approach by Aditi Site, Elena Simona Lohan, Jari Nurmi

“…E-health sensors and wearables play an important role in the detection and classification of many chronic diseases. …”
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A Fast Fault Detection Scheme for Power Converters In Distributed Generation Systems by Gustavo M. S. Azevedo, Marcelo C. Cavalcanti, Francisco A. S. Neves, Fabricio Bradaschia

“… In this paper, a fault detection algorithm based on voltage disturbances is proposed and analyzed. …”
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Sentiment Modeling of Instagram Users Towards Traditional and Modern Body Scrubs Using the Naive Bayes Algorithm by Mardiana Mardiana, Kusrini Kusrini

“…The results indicate that neutral sentiment dominates, followed by negative and positive sentiments. The Naive Bayes algorithm demonstrated strong performance, particularly in detecting negative and neutral sentiments, but exhibited a lower recall rate for positive sentiments. …”
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A Deep Learning Segmentation Model for Detection of Active Proliferative Diabetic Retinopathy by Sebastian Dinesen, Marianne G. Schou, Christoffer V. Hedegaard, Yousif Subhi, Thiusius R. Savarimuthu, Tunde Peto, Jakob K. H. Andersen, Jakob Grauslund

“…Abstract Introduction Existing deep learning (DL) algorithms lack the capability to accurately identify patients in immediate need of treatment for proliferative diabetic retinopathy (PDR). …”
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Detecting memberships in multiplex networks via nonnegative matrix factorization and tensor decomposition by Fengqin Tang, Xiaozong Wang, Xuejing Zhao, Chunning Wang

“…Multiplex networks provide a powerful data structure for capturing diverse relationships among nodes, and the challenge of community detection within these networks has recently attracted considerable attention. …”
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