Search Results - (( using function new algorithm ) OR ( image classification using algorithm ))
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1
Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang
Published 2013“…Due to the complexity of hypergeometric functions, existing invariant algorithms are slow. …”
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2
A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…This study investigates a new approach in image classification. Two classifiers were used to classify SPOT 5 satellite image; Decision Tree (DT) and Support Vector Machine (SVM). …”
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3
Support vector classification of remote sensing images using improved spectral Kernels
Published 2008“…Subsequently we use mixtures of these kernels to derive new and more efficient kernels for classification. …”
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4
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…To overcome such challenges, this study attempts to comprehend and improve the remote sensing technology for rooftop classification using the Worldview-3 (WV-3) image and object-based image analysis (OBIA) method. …”
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5
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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6
Neural network paradigm for classification of defects on PCB
Published 2003“…A defective PCB image is used to ensure the function of the proposed technique.…”
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7
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. 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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8
RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
Published 2018“…The RMIL uses the value of adaptive gain parameter in the activation function to modify the gradient based search direction. …”
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9
Implementation of vision-assisted path planning system for bulk die sorting in semiconductor industry
Published 2018“…Firstly, the wafer image is acquired using the image mosaicing method. …”
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10
Implementation of vision-assisted path planning system for bulk die sorting in semiconductor industry
Published 2018“…Firstly, the wafer image is acquired using the image mosaicing method. …”
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11
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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12
Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
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13
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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14
Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine
Published 2019“…The RX_myKarve is an extended framework from X_myKarve, which consists of the following key components: (i) an Extreme Learning Machine (ELM) neural network for clusters classification using three existing content-based features extraction (Entropy, Byte Frequency Distribution (BFD) and Rate of Change (RoC)) to improve the identification of JPEG images content and support the reassembling process; (ii) a genetic algorithm with Coherence Euclidean Distance (CED) matric and cost function to reconstruct a JPEG image from a set of deformed and fragmented clusters in the scan area. …”
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15
New species orchid recognition system using convolutional neural network / Annisa Atikah Mohd Fadzil and Itaza Afiani Mohtar
Published 2021“…Every year, about a hundred of new species names are published. The study is to determine whether the orchid species can be recognized using a convolutional neural network algorithm and to test the accuracy of the classification model. …”
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16
Face emotion recognition using artificial intelligence techniques
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17
Secure Access To Authorized Resources Based On Fingerprint Authentication
Published 2003“…Passwords are frequently used to control access to restricted functions. …”
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18
Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images
Published 2019“…This dissertation presents a Modified Piecewise Linear Mapping and Local Otsu Segmentation as a pre-processing and segmentation approach for the HEp-2 images. Proposed pre-processing focus on minimizing the existence of noise in the background and stretching the cell’s contrast by using piecewise linear mapping function technique. …”
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19
Identifying the mechanism to forecast the progression of Alzheimer’s disease from mild cognitive impairment using deep learning
Published 2022“…This study also implemented a CNN algorithm based on 3D ResNet-18 model using weights from ImageNet for the classification task of CN vs AD and sMCI vs pMCI. …”
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Final Year Project / Dissertation / Thesis -
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Electrocardiogram based heart disease diagnosis using artificial intelligence
Published 2015“…Accordingly, the first step is an image segmentation method using proposed thresholding algorithms has been used to locate objects and boundaries of the ECG signal and background grid lines in the ECG images. …”
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