Search Results - (( user evaluation result algorithm ) OR ( image classification system algorithm ))*
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Leaf condition analysis using convolutional neural network and vision transformer
Published 2024“…Besides, existing leaf disease detection programs do not provide an optimized user’s experience. As a result, although customers may receive an excellent interactive features programme, the backend algorithm is not optimized. …”
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A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid
Published 2020“…Furthermore, the accuracy of the image classification can be improved by increasing the number of datasets, the distance of images from the camera, and the labelling process. …”
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Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz
Published 2020“…Functionality test was done in order to evaluate the system. The result of the functionality test is most of the user are satisfy with the system. …”
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Automated leaf alignment and partial shape feature extraction for plant leaf classification
Published 2019“…The well-known Flavia dataset has been selected for the evaluation of the proposed system. The experimental results indicate the ability of the proposed alignment algorithm to align leaves with different shapes and maintain a correct classification accuracy regardless of the orientation of the input leaf samples. …”
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Malay festive seasons food recognition for calorie detection / Nurul Hafiza Basiruddin
Published 2021“…As color plays an important role in differentiating the type of food, therefore this research aims to implement Color Feature Extraction Method after performing segmentation techniques during the pre-processing phase where each color from the images will be extracted individually. Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification which is the part of the Support Vector Machine (SVM) algorithm. …”
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Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images
Published 2025“…A hybrid segmentation technique, fuzzy c-means with active contour (FCMAC), is proposed to enhance lesion localization accuracy. For classification, the system evaluates traditional machine learning algorithms like support vector machine (SVM) and k-nearest neighbor (KNN), alongside deep learning models such as convolutional neural network (CNN) and bilayered neural network (BNN). …”
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A hierarchical deep convolutional neural network for asphalt pavement crack detection and classification / Nor Aizam Muhamed Yusof
Published 2021“…To ease these processes, this study introduces a new app, CrackLabel, that can automatically label patches in the crack images into two groups, crack and non-crack. The CrackLabel utilises a special design image thresholding algorithm known as Global and Lower Quartile Average Intensity (GLQAI). …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Malay festive seasons food recognition for calorie detection using SVM and ECOC approaches / Nurul Hafiza Binti Basiruddin, Zalikha Zulkifli and Samsiah Ahmad
Published 2022“…As color plays an important role in differentiating the type of food, this research aims to implement Color Feature Extraction Method after performing segmentation techniques during the pre-processing phase, where each color from the images is extracted individually. Then the result from the Color Feature Extraction Method is used to identify the type of food by using Error-Correcting Output Codes (ECOC) classification, which is part of the Support Vector Machine (SVM) algorithm. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. …”
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
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The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment
Published 2007“…However, hyperspectral image systems produce large data sets that are not easily interpretable by visual analysis and therefore require automated processing 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“…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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A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim
Published 2015“…Thus, the involvement of information technology is highly demanded in introducing reliable, simple and accurate computer systems. This study presents an algorithm for nosologic segmentation of primary brain tumors on Magnetic Resonance Imaging (MRI) brain images. …”
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Vision-based egg grade classifier
Published 2023“…Coordinate measuring machines; Human computer interaction; Image classification; Image enhancement; Intelligent systems; Medical imaging; Military photography; Classification algorithm; Digital image processing technique; Human computer interfaces; Image filtering; Image processing technique; Industrial inspections; Object classification; Vision systems; Image processing…”
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Trademark image classification approaches using neural network and rough set theory
Published 2003“…Two new approaches are proposed to classify trademark images. The approaches contain five major stages, namely: image acquisition, image preprocessing, feature extraction, data transformation and classification. …”
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An internet of things based for smart recycle waste classification / Akmal Md Nasir
Published 2023“…To accurately categorise waste into the categories of metal, paper, plastic, and maybe other waste types, the system uses an image classification model based on the ResNet algorithm. …”
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Laser-induced backscattering imaging for classification of seeded and seedless watermelons
Published 2017“…Backscattering images were obtained from seeded and seedless watermelon samples through a laser diode emitting at 658 nm using a backscattering imaging system developed for the purpose. …”
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