Search Results - (( java application optimisation algorithm ) OR ( missing image classification algorithm ))
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An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images
Published 2012“…Therefore, an algorithm for PCB defect classification is presented that consists of well-known conventional operations, including image difference, image subtraction, image addition, counted image comparator, flood-fill, and labeling for the classification of six different defects, namely, missing hole, pinhole, underetch, short-circuit, open-circuit, and mousebite. …”
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Extreme learning machine classification of file clusters for evaluating content-based feature vectors
Published 2018“…The files are allocated in a continuous series of clusters. The ELM algorithm is applied to the DFRWS (2006) dataset and the results show that the combination of the three methods produces 93.46% classification accuracy.…”
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Vehicle classification technique for automated road traffic census
Published 2014“…This thesis proposes the development of vehicle classification technique for automated road traffic census prototype to replace manually vehicle classification by applying morphological techniques for image classification. …”
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Final Year Project Report / IMRAD -
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AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION
Published 2022“…The developed algorithm is trained on the augmented Chinese Power Line Insulator Dataset (CPLID) that consisted of normal and missing cap insulator images. …”
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Final Year Project Report / IMRAD -
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Efficient classifying and indexing for large iris database based on enhanced clustering method
Published 2018“…Explosive growth in the volume of stored biometric data has resulted in classification and indexing becoming important operations in image database systems. …”
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Classification of JPEG files by using extreme learning machine
Published 2018“…This paper proposes an Extreme Learning Machine (ELM) algorithm to assign a class label of JPEG or Non-JPEG image for files in a continuous series of data clusters. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Deep learning-based classification of breast tumors in ultrasound images / Ayub Ahmed Omar
Published 2022“…The U-Net model is used to locate tumor growth in original medical images because of its capacity to do classification on each pixel in the input image and produce input and output images that are the same size. …”
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Thesis -
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model
Published 2023“…Finally, the classification is implemented using an ensemble classifier, deep learning instantaneously trained a neural network and an Autoencoder-based Recurrent Neural Network (ARNN) classification algorithm. …”
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Robust partitioning and indexing for iris biometric database based on local features
Published 2018“…Explosive growth in the volume of stored biometric data has resulted in classification and indexing becoming important operations in image database systems. …”
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Breast cancer detection by using associative classifier with rule refinement method based on relevance feedback
Published 2022“…Several researchers have proposed the use of associative classifier that generates strong associations between features and reveals hidden relationship that can be missed by other classification algorithms. However, the effectiveness of an associative classifier depends largely on the generalized rules based on training data. …”
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Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine
Published 2019“…However, completely recovering intertwined Bifragmented JPEG images into their original form without missing any parts or data of the image is a challenging due to the intertwined case might occur with non-JPEG images such as PDF, Text, Microsoft Office or random data. …”
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Early Detection of Breast Cancer with Microcalcifications on Mammography Using Deep Learning
Published 2025“…Conventional diagnostic procedures sometimes face obstacles due to the complexity and nuance of MC patterns, resulting in higher percentages of missed diagnoses and false positives. This paper develops a deep convolutional neural network (CNN) model to increase the detection and classification accuracy of microcalcifications (MCs) in mammographic images. …”
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Conference or Workshop Item -
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Prediction of breast cancer diagnosis using machine learning in Malaysian women
Published 2024“…Five factors affecting mammographic density were age, number of children, body mass index, menopause status, and breast imaging-reporting and data system (BI-RADS) classification. …”
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Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm
Published 2019“…The results include flood probabilities and prediction analysis using proposed algorithm.…”
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Proceeding Paper
