Search Results - (( image classification using algorithm ) OR ( based visualization learning algorithm ))
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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Visual codebook analysis in image understanding / Hoo Wai Lam
Published 2015“…As a resultant of that, visual codebook will learn wrong information, and thus affects the image classification performance. …”
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Extremal region selection for MSER detection in food recognition
Published 2021“…Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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Automatic topic-based web page classification using deep learning
Published 2023“…However, there is lack of study that review classification of web pages using deep learning. In this study, the automatic topic-based classification of web pages utilising deep learning that has been proposed by many key researchers are reviewed. …”
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Automatic Topic-Based Web Page Classification Using Deep Learning
Published 2023“…However, there is lack of study that review classification of web pages using deep learning. In this study, the automatic topic-based classification of web pages utilising deep learning that has been proposed by many key researchers are reviewed. …”
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The first algorithm locates interest points in food images using an MSER. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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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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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…To overcome this problem, in recent years, researchers obtained some achievements with combination of invariant local features such as Scale Invariant Feature Transform (SIFT) with global feature of leaf images. Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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Extremal Region Selection for MSER Detection in Food Recognition
Published 2021“…Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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Malware visualizer: A web apps malware family classification with machine learning
Published 2021“…This project uses three classification algorithm which are Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). …”
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Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques
Published 2025“…The k-means clustering algorithm is then applied to group visually similar chart images. …”
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Decision tree as knowledge management tool in image classification
Published 2008“…Expert System has been grown so fast as a science that study how to make computer capable of solving problems that typically can only be solved by expert.It has been realized that the biggest challenge of developing expert system is the process include expert’s knowledge into the system.This research tries to model expert’s knowledge management using case based reasoning method.The knowledge itself is not inputted directly by the expert, but rather the system will learn the knowledge from what the expert did to the previous cases.This research takes image classification as the problem to be solved.As the knowledge development technique, we build decision tree by using C4.5 algorithm.Variables used for building the decision tree are the image visual features.…”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticilliumwilt (PVw) and Potato Healthy (PH) class. …”
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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION
Published 2021“…A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. …”
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Texture-based classification of workpiece surface images using the support vector machine
Published 2015“…Machine vision can be used to semi- or fully automate this identification process by firstly extracting features from captured workpiece images, followed by analysis using machine learning algorithms. This enables inspection to be performed more reliably with minimal human intervention. …”
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