Search Results - (( using vectorization learning algorithm ) OR ( _ visualization system algorithm ))

Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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Wearable based-sensor fall detection system using machine learning algorithm by Ishak, Anis Nadia, Habaebi, Mohamed Hadi, Yusoff, Siti Hajar, Islam, Md. Rafiqul

“…To prevent such kinds of deadly scenarios, a reliable fall detection system must be developed to help many lives. In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. …”
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Defect green coffee bean detection using image recognition and supervised learning by Shafian Izan Sofian

“…Therefore, in this research project, the process will be conducted by using an image classifier with the model of a machine learning algorithm which the candidates comprise of Support Vector Machine, k-Nearest Neighbour and Decision Tree. k-nearest neighbour has the highest F1-score (0.51) than the other two algorithms (Support Vector Machine: 0.50, and Decision Tree: 0.48). …”
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Place recognition using semantic concepts of visual words by Rostami, Vahid, Ramli, Abdul Rahman, Samsudin, Khairulmizam, Saripan, M. Iqbal

“…Specifically, the k-mean algorithm is firstly applied to quantize the low-level visual features as bag-of-visual-words (BOVW). …”
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Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

“…The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…This study proposed an integrated system for EEG signals pre-processing by using machine learning algorithms in the identification of artifactual components during the process of Wavelet-ICA. …”
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Diabetes risk prediction system and data visualization / Azizah Mohamad Imran and Hawa Mohd Ekhsan by Mohamad Imran, Azizah, Mohd Ekhsan, Hawa

“…To determine Diabetes, the prediction model used and compared different machine learning algorithms such as Logistic Regression (LR) and Support Vector Machine (SVM). …”
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Comparative Analysis of Cervical Cell Classification Using Machine Learning Algorithms by Wan Azani Mustafa, Khalis Khiruddin, Khairur Rijal Jamaludin, Firdaus Yuslan Khusairi, Shahrina Ismail

Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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Investigation and analysis of crack detection using UAV and CNN: A case study of Hospital Raja Permaisuri Bainun by Goh, Wei Sheng, Wan Din, Wan Isni Sofiah, Waseem, Quadri, Zabidi, A.

“…Automated crack detection using Machine Learning Algorithms (MLA), especially a Conventional Neural Network (CNN), along with an Unmanned Aerial Vehicle (UAV), can be effective and both can efficiently work together to detect the cracks in buildings using image processing techniques. …”
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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

“…Moreover, skin lesion images are clustered based on fused color, pattern and shape based features. A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
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Malware Detection using Deep Learning (DL) by Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo

Predicting the onset of acute coronary syndrome events and in-hospital mortality using machine learning approaches / Song Cheen by Song , Cheen

“…This web system was developed using a prototype-driven approach, emphasizing user feedback, and evaluated using the System Usability Scale (SUS). …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”

Proactive thermal management of photovoltaic systems using nanofluid cooling and advanced machine learning models by Masalha, Ismail, Alahmer, Ali, Badran, Omar, Al-Khawaldeh, Mustafa Awwad, Masuri, Siti Ujila, Maaitah, Hussein

“…Using 0.1% TiO2 nanofluid at 5 L min−1 reduced PV surface temperature by 23.72% and improved power output by 16.36% compared to the uncooled system. …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…In this article, we have focused on developing a model of angular nature that performs supervised classification. Here, we have used two shifting vectors named Support Direction Vector (SDV) and Support Origin Vector (SOV) to form a linear function. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”

Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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