Search Results - (( java segmentation using algorithm ) OR ( program scheme learning algorithm ))

Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Functional programming paradigm with scheme programming language / Jamal Othman by Othman, Jamal

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Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

“…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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Development of a software for simulating active force control schemes of a two-link planar manipulator by Mailah, Musa, Poh, Yang Liang

“…On Top Of That, The Graphical Results Can Be Observed And Analysed On-Line While The Program Is Running. By Using Matlab And Its Gui Facility, All The AFC Schemes Already Described In The Previous Works Such As The AFC With Crude Approximation Method, AFC And Iterative Learning (Afcail), AFC And Neural Network (Afcann), AFC And Fuzzy Logic (Afcafl), And AFC And Genetic Algorithm (Afcaga) Schemes Were Linked Into A Single Menu-Driven Program Where Each Of The Scheme Can Be Easily Selected And Executed By The User. …”
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Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

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Development of a software for simulating active force control schemes of a two–link planar manipulator by Mailah, Musa, Poh, Yang Liang

“…On top of that, the graphical results can be observed and analysed on–line while the program is running. By using MATLAB and its GUI facility, all the AFC schemes already described in the previous works such as the AFC with crude approximation method, AFC and Iterative Learning (AFCAIL), AFC and Neural Network (AFCANN), AFC and Fuzzy Logic (AFCAFL), and AFC and Genetic Algorithm (AFCAGA) schemes were linked into a single menu–driven program where each of the scheme can be easily selected and executed by the user. …”
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Genetic programming based machine learning in classifying public-private partnerships investor intention / Ahmad Amin ... [et al.] by Amin, Ahmad, Rahmawaty, Rahmawaty, Lautania, Maya Febrianty, Abdul Rahman, Rahayu

“…The PPP data was analyzed in this study using two machine learning approaches, Genetic Programming and conventional machine learning, with testing results showing that all machine learning algorithms from both approaches achieved high accuracy rates of over 80%, with the Genetic Programming machine learning outperformed the conventional approach. …”
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Adaptive algorithms for automated intruder detection in surveillance networks by Ahmed, Tarem, Pathan, Al-Sakib Khan, Ahmed, Supriyo

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Source code classification using latent semantic indexing with structural and frequency term weighting by Yusof, Yuhanis, Alhersh, Taha, Mahmuddin, Massudi, Mohamed Din, Aniza

“…Based on the undertaken experiment the LSI classifier is noted to generate a higher precision and recall compared to the C4.5 algorithm. Furthermore,it is also learned that the use of structural information in the weighting scheme contribute to a better classification.…”
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Assessment of using EZ-Prog: an easy color schematic model for programming problem solving by Siti Nordianah Hai Hom, Hasnul Hadi Ibrahim, Abrizah Ibrahim, Mudiana Mokhsin, Corrienna Abdul Talib

“…The implications of this study indicate that EZ-Prog can be used in learning and teaching algorithms, especially programming problems. …”
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Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam by Toghroli, Ali, Suhatril, Meldi, Ibrahim, Zainah, Safa, Maryam, Shariati, Mahdi, Shamshirband, Shahaboddin

“…In comparison to the other widely used conventional learning algorithms, the ELM has a much faster learning ability.…”
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Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Application Of The Differential Quadrature Method To Problems In Engineering Mechanics by Fakir, Md.Moslemuddin

“…This method is a simple and direct technique, which can be applied in a large number of cases to circumvent the difficulties of programming complex algorithms for the computer, as well as excessive use of storage and computer time. …”
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