Search Results - (( data visualization based algorithm ) OR ( level classification based algorithm ))
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…The textural features extracted are based on the first-order statistics and second-order statistics computed from grey level co-occurrence matrices (GLCM). …”
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Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI)
Published 2024“…Weka is a strong data mining and machine learning program including algorithms for data preparation, classification, regression, clustering, 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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Thesis -
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Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics
Published 2023“…In terms of reproducibility, data flow control, data exploration, analysis and visualization, KNIME Analytics Platform provided great convenience in connecting tools graphically and ensuring the same results on different operating systems. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Thesis -
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Urban landcover features identification utilizing multiband combinations and multi-level image segmentation for objectbased classification / Nurhanisah Hashim
Published 2018“…By adopting object based approached instead of pixel based will avoid the 'salt and pepper' effect that will decrease the accuracy of land-cover classification. …”
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10
Segmentation Assisted Object Distinction For Direct Volume Rendering
Published 2013“…A set of image processing techniques are creatively employed in the design of K-means based hybrid segmentation algorithm.…”
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IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management
Published 2025“…Advanced data preprocessing, such as augmentation and normalization, ensures robust model training, while optimized algorithms guide waste sorting based on classification results. …”
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Proceeding -
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A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping
Published 2016“…The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. …”
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
Published 2020“…In this research, a fully automated system is presented to automatically detect the various states of the epileptic seizure. This study is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. …”
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Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials
Published 2013“…Therefore, by removmg the low frequency signals, the intemal defect detectability can be improved. Moreover, the classification of an input pattem based on the closest neighbours of the point of interest provides more accurate defect detection in comparison with the classification based on experience data as the defect pattems vary on circumstances in ultrasonic NDE problems.…”
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15
P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…By reduction of recording EEG channels in the single trial based algorithms, the processing time of P300 detection decrease dramatically. …”
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Thesis -
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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. …”
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…In order to reduce the training time and computational cost of the algorithm, Principal Components Analysis (PCA) pretraining strategy is deployed to obtain data adaptive filter banks. …”
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A stable and accurate wavelet-based method for noise reduction from hyperspectral vegetation spectrum
Published 2015“…SLWT incorporates the advantages of both SWT and LWT methods, including a translation invariance property and a fast simple algorithm. Experimental results show that SLWT highly outperforms other wavelet-based methods in terms of accuracy and visual quality. …”
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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning
Published 2023“…This method adeptly navigates the hurdles of data scarcity, diverse human behaviors, and visual variations typical in manufacturing environments. …”
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Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation
Published 2013“…Results confirmed the usefulness and efficiency of spectra-based classification approach for fast screening of BSR.…”
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Thesis
