Search Results - (( _ evaluation index algorithm ) OR ( image classification based algorithm ))
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1
An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The results are evaluated by receiver operating characteristic (ROC) graph and the existing technique that gives the best performance is landscape expansion index. …”
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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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Lung cancer medical images classification using hybrid CNN-SVM
Published 2021“…This paper presents an image classification method based on the hybrid Convolutional Neural Network (CNN) algorithm and Support Vector Machine (SVM). …”
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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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Novel techniques for enhancement and segmentation of acne vulgaris lesions
Published 2013“…Methods: For the first objective, an algorithm is developed based on the theory of high dynamic range (HDR) images. …”
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Ripeness level classification for pineapple using RGB and HSI colour maps
Published 2013“…An algorithm is developed using MATLAB software to evaluate features based on an image of the pineapple. …”
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Monitoring the impacts of drought on land use/cover: a developed object-based algorithm for NOAA AVHRR time series data
Published 2011“…As a novel idea in this study, it developed a new object-based classification algorithm for AVHRR (Advanced Very High Resolution Radiometer) data. …”
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Automated Segmentation And Classification Technique For Brain Stroke
Published 2019“…The algorithm performance has been evaluated using Jaccard Index, Dice Coefficient (DC) and both false positive rate (FPR) and false negative rate (FNR). …”
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“myHerbs”: A mobile based application for herbal leaf recognition using sift / Nur Nabilah Abu Mangshor …[et al.]
Published 2020“…In addition, it also contributes to the exploration and implementation of learning algorithm in mobile-based application.…”
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An evaluation of feature selection methods on multi-class imbalance and high dimensionality shape-based leaf image features
Published 2017“…Multi-class imbalance shape-based leaf image features requires feature subset that appropriately represent the leaf shape.Multi-class imbalance data is a type of data classification problem in which some data classes is highly underrepresented compared to others.This occurs when at least one data class is represented by just a few numbers of training samples known as the minority class compared to other classes that make up the majority class.To address this issue in shapebased leaf image feature extraction, this paper discusses the evaluation of several methods available in Weka and a wrapperbased genetic algorithm feature selection.…”
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Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification
Published 2023“…The Viola-Jones algorithm is then used for face detection on the processed grayscale images. …”
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Evaluation of land use land cover changes impacts on water quality at Nerus River using geospatial techniques / Noor Azzatul Najwa Azman
Published 2021“…The method that used to do the classification for each year is supervised classification. …”
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…For identification, the image processing involves process of image pre-processing, feature extraction and classification. …”
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Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging
Published 2022“…Multimodal data fusion based on three different CNN architectures including ResNet, VGG16, and InceptionV3 was designed for the classification of pineapple varieties with classification rate up to 92 %. …”
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Introducing new statistical shape based and texture feature extraction methods in the plant species recognition system
Published 2013“…The results show the outperformance of the two proposed methods for image processing and optimized classifier for classification part. …”
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Grain recognition based on colour and shape analysis
Published 2020“…This work aims to contribute to an automatic grain recognition using an image-based query instead of a text-based query. …”
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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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Comparison of Landsat 8, Sentinel-2 and spectral indices combinations for Google Earth Engine-based land use mapping in the Johor River Basin, Malaysia
Published 2021“…This study aims to improve the land use mapping in a tropical region based on the GEE platform. Seven satellite images and indices combinations include Landsat 8 (C1), Sentinel-2 (C2), Landsat 8+Sentinel-2 (C3), Landsat 8+Indices (C4), Sentinel-2+Indices (C5), Landsat 8+Sentinel-2+Indices (C6), Normalized Difference Vegetation Index (NDVI)+Normalized Difference Water Index (NDWI)+Enhanced Vegetation Index (EVI)+Elevation (C7) were developed to evaluate the best combination for land use mapping in the Johor River Basin (JRB), Malaysia. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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