Search Results - (( features detection method algorithm ) OR ( data visualization learning algorithm ))
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Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi
Published 2022“…This problem occurs due to lacking of existing system in detecting children image in a car. Therefore, this study aims to detect the existence of "in-car-abandoned children" using deep learning algorithm. …”
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Cabbage disease detection system using k-NN algorithm
Published 2022“…Then, the segmented cabbage sample will use the GLCM method for feature extraction. It is a method of extracting second-order statistical texture features to detect diseases more efficiently. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. …”
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A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. …”
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A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. …”
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A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. …”
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A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. …”
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A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. …”
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A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. …”
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Defects identification on semiconductor wafer for yield improvement using machine learning / Pedram Tabatabaeemoshiri
Published 2025“…This work presents a novel graph-based semi-supervised learning (GSSL) algorithm designed for wafer defect detection. …”
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Hybrid sampling and random forest machine learning approach for software detect prediction
Published 2019“…The machine learning model is miss leaded by these imbalanced data. …”
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Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows
Published 2026“…The above are the major components of a vision system: Data Acquisition, Multimodal Preprocessing, Cross-Media Feature Extraction, Emotional Value Detection and Moderation, and Interpretability and Visualization. …”
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Application of target detection method based on convolutional neural network in sustainable outdoor education
Published 2023“…The model can recognize underwater organisms local, global, and visual features. Different recognition methods have certain advantages in accuracy, speed, and other aspects. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining
Published 2025“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning
Published 2023“…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…This paper surveyed studies on skin cancer detection using deep learning to assess the features and advantages of other techniques. …”
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A Symbol Recognition System for Single-Line Diagrams Developed Using a Deep-Learning Approach
Published 2023“…Featured Application: The present study is among the first research efforts to generate augmented datasets of complex single-line diagrams to detect symbols using deep-learning-based algorithms. …”
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