Search Results - (( developing pervasive learning algorithm ) OR ( java segmentation based algorithm ))
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Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…The proposed ANPR algorithm was based on an open source image processing library called Leptonica and OCR library called Tesseract. …”
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Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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LINGUISTIC FUZZY MODELING IN LASER MACHINING QUALITY EVALUATION
Published 2007“…The aim of this scientific research is to design knowledge based linguistic rules, algorithm, architecture & learning ability and further develop fuzzy model for laser machining kerf edge quality prediction. …”
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Fuzzy expert system modeling of laser processing
Published 2009“…The objective of the paper is: to design knowledge based rules, algorithm, architecture & learning ability to develop fuzzy surface roughness predictive model for laser machining; to develop fuzzy predictive model using design parameters which were critically analyzed; to make a comparative study of the observed and modelled surface roughness output of 5mm Mn-Mo pressure vessel plate. …”
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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…Missing data is a pervasive challenge in diverse datasets accross various domains. …”
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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…Missing data is a pervasive challenge in diverse datasets, often resulting from human error, system faults, and respondent non-response. …”
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