Search Results - (( data detection based algorithm ) OR ( data visualization learning algorithm ))
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Wearable based-sensor fall detection system using machine learning algorithm
Published 2021“…In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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Cabbage disease detection system using k-NN algorithm
Published 2022“…It is a method of extracting second-order statistical texture features to detect diseases more efficiently. Finally, the KNN algorithm will be used to classify the disease based on sample nature and a cabbage disease data set. …”
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A Hybrid Artificial Intelligence Model for Detecting Keratoconus
Published 2023“…This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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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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Conference or Workshop Item -
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Fast shot boundary detection based on separable moments and support vector machine
Published 2021“…As a result, the computational cost is reduced in the subsequent stages. Finally, machine learning statistics based on the support vector machine is implemented to detect the cut transitions. …”
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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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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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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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Deep learning-based water segmentation for autonomous surface vessel
Published 2020“…Classical computer vision algorithms for detection holds limitation in robustness and scalability. …”
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Proceeding Paper -
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Thyroid Insight: navigating disease data through interactive visualization with prediction
Published 2025“…The dashboard employs Microsoft Power BI for visualizations and the Random Forest algorithm for predictive modelling. …”
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Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification
Published 2023“…Despite extensive research employing machine learning algorithms like convolutional neural networks (CNN), challenges remain concerning input data processing, emotion classification scope, data size, optimal CNN configurations, and performance evaluation. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. …”
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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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Identifying suicidal ideation through twitter sentiment analysis using Naïve Bayes / Annasuha Atie Atirah Alias
Published 2023“…By harnessing natural language processing techniques and data visualization tools, the project seeks to provide user-friendly solution for early detection and prevention of suicidal intentions expressed on social media. …”
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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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