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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification
Published 2023“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…The CNN algorithm produces better results with an accuracy of 97.07%, compared with the SVM algorithm. …”
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Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman
Published 2024“…In response to the unprecedented challenges posed by the COVID-19 pandemic, this research project presents a systematic approach to outbreak prediction, specifically advocating for the implementation of Support Vector Machine (SVM) algorithms. …”
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Thesis -
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Classification Of Cervical Cancer Stage From Pap Smear Tests
Published 2019“…The proposed approach will implement stages of image pre-processing, feature selection and extraction as well as classification of classes. …”
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Final Year Project -
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…Statistical techniques such as Anisotropic Diffusion Filter (ADF), local contrast enhancement, and haze reduction in the CIELAB colour space, are incorporated in the proposed algorithms for the pre-processing step. Hair removal is implemented through black-hat morphological processing and total variation based inpainting. …”
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Thesis -
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Camera Independent Face Recognition Algorithm In Visual Surveillance
Published 2015“…The flandmark facial landmark detector is implemented to determine the location of the eyes and new face images are obtained by cropping the HE pre-processed images. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…According to the obtained results, the pre-developed ANN achieved generally more reliable capability of prediction in compare to SVM and CART. …”
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Automatic Classification of Cervix Type
Published 2019“…Due to that, in this study, few algorithms were developed by using image classification methods to correctly classify the cervix types based on cervical images by using segmentation and classification method. …”
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Final Year Project -
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EEG-based emotion recognition using machine learning algorithms
Published 2024“…Thus, this project proposed an optimised machine learning algorithms to classify emotion by analysing brain activity using Electroencephalogram (EEG) signals. …”
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Final Year Project / Dissertation / Thesis -
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Raspberry Pi-Based Finger Vein Recognition System Using PCANet
Published 2018“…For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. An enhancement version for kNN algorithm, k-General Nearest Neighbours (kGNN) have been proposed at initial stage. …”
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Monograph -
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Attacks detection in 6G wireless networks using machine learning
Published 2023“…Correlation Feature Selection algorithm (CFS) is used to implement the suggested hybrid strategy. …”
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Proceeding Paper -
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…SOM and K-Means are integrated as a clustering algorithm to produce a granular input, while SVM is then used as a classifier. …”
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Monograph -
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A robust illumination-invariant face recognition based on fusion of thermal IR, maximum filter and visible image
Published 2020“…To create a more robust face recognition with illumination invariant, this paper proposed an algorithm using a triple fusion approach. We are also implementing a hybrid method that combines the active approach by implementing thermal infrared imaging and also the passive approach of Maximum Filter and visual image. …”
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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. …”
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
Published 2019“…This is taking advantage on the discriminative feature provided by both methods, statistical and CSP filter, which is expected to increase the accuracy of the eye state classification algorithm. The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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