Search Results - (( java segmentation using algorithm ) OR ( basic using solid algorithm ))
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1
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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Thesis -
2
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Book -
3
Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Proceeding Paper -
4
SOLID-STATE MP3 PLAYER
Published 2005“…A simple block diagram of a complete player basically consists of • A solid-state memory to store data…”
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Final Year Project -
5
TEMPERATURE CONTROLLER FOR AUTOMOTIVE ENGINE RESEARCH
Published 2009“…The main objective of this project is to investigate different temperature control algorithm and to implement on hardware by fabricating a controller using a temperature control IC. …”
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Final Year Project -
6
A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
Published 2023“…The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm. …”
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Thesis -
7
INDOOR LOCATION SENSING USING RADIO FREQUENCY NETWORK
Published 2007“…The benefit of this project is that it provides a foundation in the basic of locating objects in a closed area. The flowchart for the main program and hence, the programming of the calculations algorithm has been done and tested using user simulated digital control input. …”
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Final Year Project -
8
Water Quality Index Using Modified Random Forest Technique: Assessing Novel Input Features
Published 2024journal::journal article -
9
Predictive modeling and feature attribution of CO₂ adsorption on LDH-derived materials using machine learning approach
Published 2025“…The findings revealed that CatBoost is most suitable with R2 of 0.99 for training and 0.87 for test, and RMSE of 0.184 compared to the other 5 algorithms. AdaBoost, XGBoost, GBDT, LightGBM, and RF performed in an acceptable range. …”
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