Search Results - (( based evaluation from algorithm ) OR ( image classification based algorithm ))
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…All the algorithms were pretrained from ImageNet data-base before training with the wafer defect images. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…It involves identifying and isolating relevant information from the images that classification algorithms can use to distinguish between different fruit categories. …”
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Laser-induced backscattering imaging for classification of seeded and seedless watermelons
Published 2017“…The LDA and kNN-based algorithms also obtained quite high classification accuracies with all the accuracies above 90%. …”
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A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim
Published 2015“…The CAPSOCA was proven to be the best algorithm for nosologic segmentation of primary brain tumors from the MRI images data. …”
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The performance of algorithms was measured based on classification accuracy, error rate, and precision and recall. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are two stages in the proposed classification system. Firstly, the 1D-LBP algorithm is used to extract the features of the normalized iris images and save the data in a text file according to the subject and the combinations to evaluate for the next stage. …”
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Classification of Emphysema Patterns in Computed Tomography Based On Gabor Filter
Published 2015“…One of the main processing technique in CAD is texture classification and analysis. In this research, a Gabor-based emphysema classification algorithm is proposed. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Published 2024journal::journal article -
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Extremal region selection for MSER detection in food recognition
Published 2021“…The performance of ERS algorithm is evaluated based on the classification performance metrics by using classification rate (CR), error rate (ERT), precision (Prec.) and recall (rec.) as well as the number of extremal regions produced by ERS. …”
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Scene illumination classification based on histogram quartering of CIE-Y component
Published 2014“…This method is a combination of physic based methods and data driven (statistical) methods that categorize the images based on statistical features extracted from illumination histogram of image. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity
Published 2018“…The objective of this research is to comparatively evaluate the effectiveness of different algorithms, method combination procedure, and their parameters towards classification accuracy. …”
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Proceeding -
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The parameters involved to estimate the mangrove age are differences feature selection and different supervised machine learning algorithm. The support vector machine (SVM) which is one of the machines learning algorithms for object-based image analysis (OBIA) method is used in this study for the classification of the mangrove from other LULC. …”
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A comparative assessment between object and pixel-based classification approaches for land-use/land-cover mapping using Spot 5 imagery
Published 2014“…In pixel-based image analysis, a supervised classification was performed using the DT classifier. …”
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Object-based imagery analysis for automatic urban tree species detection using high resolution satellite image
Published 2016“…This study also explores the use and comparison of object-based classification, and two common pixel-based classification methods namely, maximum likelihood and support vector machines based on WorldView-2 satellite imagery to evaluate the potential of the object-based in compare to pixel-based to detect urban tree species. …”
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Intelligent Color Vision System For Ripeness Classification Of Oil Palm Fresh Fruit Bunch
Published 2015“…Then, the color features of the fruit region are extracted from the images and used as inputs to an Artificial Neural Network (ANN) model learning algorithm.…”
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