Search Results - (( based classification method algorithm ) OR ( _ visualization learning algorithm ))
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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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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The performance of algorithms was measured based on classification accuracy, error rate, and precision and recall. …”
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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“…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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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…Supervised and unsupervised machine learning algorithms particularly the Support Vector Machine (SVM) and Density Based Spatial Clustering of Application with Noise (DBSCAN) are used in this study. …”
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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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A review on classifying and prioritizing user review-based software requirements
Published 2024“…Investigating the potential of emerging machine learning models and algorithms to improve classification and prioritization accuracy is crucial. …”
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Security alert framework using dynamic tweet-based features for phishing detection on twitter
Published 2019“…This model is then embedded into the detection algorithm together with the inclusion of dynamic tweet-based features which are not as part of the features used to train a classification model for phishing tweet detection. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Identifying a feature selection method with a classifier algorithm that produces high performance in mortality studies is essential and has not been reported before. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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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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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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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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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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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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Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence
Published 2024“…To address these challenges, our research introduces a hybrid approach, combining various lexicon-based sentiment and emotional analysis algorithms, thereby enhancing the reliability of customer review analysis in the gastronomy tourism sector. …”
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Enhancing minority sentiment classification in gastronomy tourism: a hybrid sentiment analysis framework with data augmentation, feature engineering and business intelligence
Published 2024“…To address these challenges, our research introduces a hybrid approach, combining various lexicon-based sentiment and emotional analysis algorithms, thereby enhancing the reliability of customer review analysis in the gastronomy tourism sector. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…We also explored five fields of dermatology using deep learning applications: (1) the classification of diseases by clinical photos, (2) der moto pathology visual classification of cancer, and (3) the measurement of skin diseases by smartphone applications and personal tracking systems. …”
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