Search Results - (( automatic classifications using algorithm ) OR ( based visualization using algorithm ))
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Automatic topic-based web page classification using deep learning
Published 2023“…The review process looked at the dataset, features, algorithm, pre-processing used in classification of web pages, document representation technique and performance of the web page classification model. …”
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Automatic Topic-Based Web Page Classification Using Deep Learning
Published 2023“…The review process looked at the dataset, features, algorithm, pre-processing used in classification of web pages, document representation technique and performance of the web page classification model. …”
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A cascading fuzzy logic with image processing algorithm-based defect detection for automatic visual inspection of industrial cylindrical object’s surface
Published 2018“…The 1st stage of fuzzy logic algorithm is used to eliminate the low noise from the captured images; however, the 2nd stage is used to differentiate between the big noise and defects on the objects. …”
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Extremal region selection for MSER detection in food recognition
Published 2021“…The performance of ERS algorithm is evaluated based on the classification performance metrics by using classification rate (CR), error rate (ERT), precision (Prec.) and recall (rec.) as well as the number of extremal regions produced by ERS. …”
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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 diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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Extremal Region Selection for MSER Detection in Food Recognition
Published 2021“…The performance of ERS algorithm is evaluated based on the classification performance metrics by using classification rate (CR), error rate (ERT), precision (Prec.) and recall (rec.) as well as the number of extremal regions produced by ERS. …”
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Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment
Published 2013“…A multi-date post-classification comparison algorithm was used to determine LULC changes in two intervals, 1986-1990, and 1990-2000. …”
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
Published 2020“…This study is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. …”
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Camera Independent Face Recognition Algorithm In Visual Surveillance
Published 2015“…Face recognition in visual surveillance has the ability to reduce crime rates in public area due to the suspect’s identity can be automatically identified in real-time using the face images captured by the surveillance camera as circumstantial evidence. …”
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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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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…In conclusion, it can be inferred from the analysis that the Random Forest model has better predictive performance compared to the rest of the pallet level partition model with a height of 12 cm used in this research. Based on the train, validation, and test sets in Random Forest, the RFID capability to determine the position of the pallet can be detected precisely.…”
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Geometry based lip reading system using Multi Dimension Dynamic Time Warping
Published 2012“…This paper describes an automatic lip reading system consisting of two main modules 1) a pre-processing module able to extract lip geometry information from the video sequence and 2) a classification module to identify the visual speech based on dynamic lip movements. …”
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A hierarchical deep convolutional neural network for asphalt pavement crack detection and classification / Nor Aizam Muhamed Yusof
Published 2021“…Therefore, in tackling these issues, this study proposes a fully automated pavement crack detection and classification using a new Deep Convolutional Neural Network architecture (DCNN) called hierarchical DCNN (Hi-DCNN). …”
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Vehicle logo recognition using whitening transformation and deep learning
Published 2019“…Unlike most of the common traditional methods that employ handcrafted visual features, our proposed method is able to automatically learn and extract high-level features for the classification task. …”
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Automatic classification of medical x-ray images
Published 2013“…These features have been exploited in different algorithms for automatic classification of medical X-ray images. …”
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A rule-based segmentation method for fruit images under natural illumination
Published 2014“…This is due to the existence of non-uniform illumination on the object surface.Technically, different illuminations lead to different intensity on the object surface colour.This condition leads to low quality segmented images and therefore reduces the accuracy of object classification.Image segmentation can be accomplished using several methods such as Otsu, K-means and Fuzzy C-means.However, these three traditional methods have limitations in producing accurate segmented areas due to the existence of illumination on the object surface.Therefore, this paper developed a rule-based segmentation method that is able to segment natural images correctly and accurately.This method uses IF-THEN algorithm to segment the images of interest object. …”
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Predictive analytics for the sentiment of malaysian place of interest using machine learning models
Published 2023“…The focus of this study is to conduct Natural Language Processing (NLP) on tweets and make a better classification of sentiment using Malaya. Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
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