Copy-Move Forgery Verification in Images Using Local Feature Extractors and Optimized Classifiers by S. B. G. Tilak Babu, Ch Srinivasa Rao

“…The paper aims to present copy-move forgery detection algorithms with the help of advanced feature descriptors, such as local ternary pattern, local phase quantization, local Gabor binary pattern histogram sequence, Weber local descriptor, and local monotonic pattern, and classifiers such as optimized support vector machine and optimized NBC. …”
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Personalized prediction of negative affect in individuals with serious mental illness followed using long-term multimodal mobile phenotyping by Christian A. Webb, Boyu Ren, Habiballah Rahimi-Eichi, Bryce W. Gillis, Yoonho Chung, Justin T. Baker

“…A range of statistical approaches, including a novel personalized ensemble machine learning algorithm, were compared in their ability to predict states of heightened negative affect. …”
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Integration of smart insoles for gait assessment in exoskeleton assisted rehabilitation by Luigi D’Arco, Haiying Wang, Huiru Zheng

“…Gait phases were identified using a Finite State Machine, with transitions guided by predictions from a fuzzy c-means clustering algorithm. …”
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Enhancing multiclass brain tumor diagnosis using SVM and innovative feature extraction techniques by Mustafa Basthikodi, M. Chaithrashree, B. M. Ahamed Shafeeq, Ananth Prabhu Gurpur

“…This research addresses the challenge of multiclass categorization by employing Support Vector Machine (SVM) as the core classification algorithm and analyzing its performance in conjunction with feature extraction techniques such as Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP), as well as the dimensionality reduction technique, Principal Component Analysis (PCA). …”
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Development of an Automated Management System for Agricultural Technologies in Horticulture by D. O. Khort, A. I. Kutyrev, I. G. Smirnov, I. V. Voronkov

“…The web application used the Model View Controller design pattern, and Bootstrap as the css framework. Data visualization from the database was carried out using cloud technology, placing the site using a set of Internet Information Services. …”
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SERLogic: A Logic-Integrated Framework for Enhancing Sequential Recommendations by Lihang Fan

“…s}$ </tex-math></inline-formula>; 3) parallel algorithm that applies the discovered <inline-formula> <tex-math notation="LaTeX">$\mathsf {TIE^{+}\!…”
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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

“…The system begins with preprocessing steps, including converting videos into image sequences, applying sliding window techniques, and converting images to grayscale, then extracting human silhouettes using binary masks. We use the GrabCut algorithm for human detection and perform skeletonization with Hough transform algorithm. …”
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The Sentiment Analysis Reviewing Indosat Services from Twitter Using the Naive Bayes Classifier by Febri Astiko, Achmad Khodar

“…This sentiment analysis uses machine learning to get patterns an model that can be used again to predict new data. …”
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Accounting Management and Optimizing Production Based on Distributed Semantic Recognition by Ruina Guo, Shu Wang, Guangsen Wei

“…To validate the proposed algorithm, this study utilizes the dataset from the UCI machine learning repository and applies it for analysis and processing. …”
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Intelligent approach to detecting online fraudulent trading with solution for imbalanced data in fintech forensics by Saad M. Darwish, Amr Ibrahim Salama, Adel A. Elzoghabi

“…Abstract Detecting online fraudulent trading in the realm of Fintech presents several challenges, primarily due to the dynamic nature of financial markets and the evolving tactics of fraudsters. Traditional machine learning algorithms trained on unbalanced datasets tend to bias towards the majority class (legitimate transactions) and may overlook minority class (fraudulent transactions) patterns. …”
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Automated Image-Based Wound Area Assessment in Outpatient Clinics Using Computer-Aided Methods: A Development and Validation Study by Kuan-Chen Li, Ying-Han Lee, Yu-Hsien Lin

“…K-means clustering is a machine learning algorithm that segments the wound region by grouping pixels in an image according to their color similarity. …”
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Synergistic Matching and Influencing Factors of Grain Production and Cropland Net Primary Productivity in the Black Soil Region of Northeast China by Quanxi Wang, Jun Ren, Maomao Zhang, Hongjun Sui, Xiaodan Li

“…This study analyzed the spatial–temporal mismatch characteristics of grain production and cropland net primary productivity (CNPP) using the gravity center model, spatial autocorrelation analysis, and spatial mismatch index (SMI), and identified the spatial heterogeneity and prediction–response relationships of influencing factors based on a geographically and temporally weighted regression (GTWR) model and boosted regression tree (BRT) machine learning algorithm. The findings indicated that grain production and CNPP have been increasing, but the overall spatial pattern of cold hotspots has not changed obviously in the BSRNC from 2000 to 2020. …”
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Towards Automated Real-Time Detection and Location of Large-Scale Landslides through Seismic Waveform Back Projection by En-Jui Lee, Wu-Yu Liao, Guan-Wei Lin, Po Chen, Dawei Mu, Ching-Weei Lin

“…We present a semiautomatic algorithm for detecting and locating landslide events using both broadband and short-period recordings and have successfully applied our system to landslides in Taiwan. …”
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An optimal federated learning-based intrusion detection for IoT environment by A. Karunamurthy, K. Vijayan, Pravin R. Kshirsagar, Kuan Tak Tan

“…This might reduce the detection performance of IDS as the system doesn’t have insightful knowledge about the new attack patterns. Analyzing and detecting intrusions by analyzing diverse attack patterns is complex for machine learning algorithms. …”
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Downscaling of Soil Moisture Map using Sentinel Radar Satellite Images and Distribution Analysis in the West of Iran by Seyed Hossein Mirmosavi, kohzad Raispour, Muhammad Kamangar

“…The micro-scale backup machine vector algorithm and the high volume resolution soil moisture dispersion map were estimated between 0.18 and 0.46 b. …”
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Personalised Affective Classification Through Enhanced EEG Signal Analysis by Joseph Barrowclough, Nonso Nnamoko, Ioannis Korkontzelos

“…This overlooks individual differences and may not accurately capture the unique emotional patterns of each person.Methods This study explored the performance of six machine learning algorithms in classifying a benchmark EEG dataset (collected with a MUSE device) for affective research. …”
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TATPat based explainable EEG model for neonatal seizure detection by Turker Tuncer, Sengul Dogan, Irem Tasci, Burak Tasci, Rena Hajiyeva

“…In this EFE model, there are four essential phases and these phases: (i) automaton and transformer-based feature extraction, (ii) feature selection deploying cumulative weight-based neighborhood component analysis (CWNCA), (iii) the Directed Lobish (DLob) and Causal Connectome Theory (CCT)-based explainable result generation and (iv) classification deploying t algorithm-based support vector machine (tSVM). In the first phase, we have used a channel transformer to get channel numbers and these values have been divided into three levels and these levels are named (1) high, (2) medium and (3) low. …”
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Artificial intelligence-based Raynaud’s quantification index (ARTIX): an objective mobile-based tool for patient-centered assessment of Raynaud’s phenomenon by Marco Di Battista, Seda Colak, Anna Howard, Francesca Donadoni, Chris Owen-Smith, Andrea Rindone, Stefano Di Donato, Collette Hartley, Lesley-Anne Bissell, Francesco Del Galdo

“…Abstract Background We aimed to develop an artificial intelligence algorithm able to assess Raynaud’s phenomenon (RP) from mobile phone photography, ensuring as a patient-centered, image-based method for RP quantification. …”
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Enhancing MANET Security Through Federated Learning and Multiobjective Optimization: A Trust-Aware Routing Framework by Saad M. Hassan, Mohd Murtadha Mohamad, Farkhana Binti Muchtar, Firoz Bin Yusuf Patel Dawoodi

“…MOO, particularly nondominated sorting genetic algorithm III, effectively balances conflicting network objectives, offering a 15% improvement in overall network performance compared with single-objective approaches. …”
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Advancing Marine Surveillance: A Hybrid Approach of Physics Infused Neural Network for Enhanced Vessel Tracking Using Automatic Identification System Data by Tasmiah Haque, Md Asif Bin Syed, Srinjoy Das, Imtiaz Ahmed

“…This paper introduces a novel approach that leverages Long Short-Term Memory (LSTM), a type of recurrent neural network, renowned for its proficiency in recognizing patterns over extended periods. Recognizing the strengths and limitations of the LSTM model, we propose a hybrid machine-learning algorithm that integrates LSTM with a physics-based model. …”
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