Search Results - (( java segmentation using algorithm ) OR ( program sample 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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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 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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The impact of virtual reality on programming algorithm courses on student learning outcomes by Dewi, Ika Parma, Ambiyar, Effendi, Hansi, Giatman, Muhammad, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…This study aims to determine the impact of VR compared to traditional learning in improving student learning outcomes on programming algorithm materials. …”
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Impact learning: A learning method from feature's impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

“…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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Impact learning : A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

“…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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Impact learning: A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Muzahid, Abu Jafar Md, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

“…Machine learning algorithms build a model from sample data, called training data, to make predictions or judgments without being explicitly programmed to do so. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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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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Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi by Mohd Pauzi, Mohd Farhan

“…Therefore, this study aims to detect the existence of "in-car-abandoned children" using deep learning algorithm. A set of children images model captured and then classified into two (2) classes; children and no-children via Convolutional Neural Network (CNN) classifier. …”
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Adopting machine learning to automatically identify a suitable surgery type for refractive error patients by Mustafa Ali Malla, Al-Beak, Omar Hussien, Duaa Mowafaq Hameed, Al-Hatab, Marwa Mawfaq Mohamedsheet, Al-Nima, Raid Rafi Omar, Mohammed Sabah Jarjees, Al-Maqsood, Khalil A. K.

“…ML is dedicated to the advancement and use of algorithms that possess the capacity to acquire knowledge from data and enhance their predictive capabilities without explicit programming. …”
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Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School by Nur Hasheena, Anuar

“…The findings indicate that learning new skills such as Computational Thinking skills (i.e., programming skill) is perceived as necessary by teachers and participants in rural school. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review by Nazir, M., Noraziah, Ahmad, Rahmah, M., Sharma, Aditi

“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Monotone Data Samples Do Not Always Produce Monotone Fuzzy If- Then Rules: Learning with Ad hoc and System Identification Methods by Chin, Ying Teh, Tay, Kai Meng, Chee, Peng Lim

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Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale by Ameenuddin Irfan, S., Fadhli, M.Z., Padmanabhan, E.

“…The application aims to develop a machine learning program using the algorithm of Support Vector Machine or Gaussian Process Regression to successfully predict the contact angle. …”
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Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

“…Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
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Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

“…Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
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Facilitating English Language teaching through AI- based drama in Palestine by Bsharat, Tahani, Sheikh Ahmad, Ismail

“…Artificial Intelligence (AI) has the potential to significantly reshape the landscape of education through the integration of AI- powered tools, personalized learning algorithms, and virtual and augmented reality. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

“…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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