Search Results - (( based evaluation case algorithm ) OR ( level classification approach algorithm ))

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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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

“…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”

Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…Furthermore, RNN and MLP-NN models in the test area showed 81.11%, and 74.56%, accuracy level, respectively. These results indicated that the proposed models with optimized hyper-parameters produced the accurate classification results. …”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

“…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH by MOHD YAKOP, SITI HAJAR

“…With the dramatic increase of imaging techniques, there is a great demand for new approaches in texture analysis. This paper presents a new approach for texture analysis using statistical method and gray level run length matrix (GLRLM) approach as the second order statistics approach. …”
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A speech enhancement framework using discrete Krawtchouk-Tchebichef Transform by Mahmmod, Basheera M.

“…As a conclusion, the proposed SEA enhances and improves noisy signals and regain clean signals with less RN and SD, reducing MN level. Moreover, best improvement in quality and intelligibility properties is obtained particularly in high noise levels.…”
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Imbalanced Classification Methods for Student Grade Prediction : A Systematic Literature Review by Siti Dianah, Abdul Bujang, Ali, Selamat, Ondrej, Krejcar, Farhana, Mohamed, Cheng, Lim Kok, Chiu, Po Chan, Hamido, Fujita

“…The study also presents the most common balancing methods published from 2015 to 2021 and highlights their impact on resolving imbalanced classification in three approaches: data-level, algorithm-level, and hybrid-level. …”
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Fingerprint classification : a BI-resolution approach to singular point extraction by Leong, Chung Ern

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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Imbalanced Classification Methods for Student Grade Prediction: A Systematic Literature Review by Abdul Bujang S.D., Selamat A., Krejcar O., Mohamed F., Cheng L.K., Chiu P.C., Fujita H.

“…The study also presents the most common balancing methods published from 2015 to 2021 and highlights their impact on resolving imbalanced classification in three approaches: data-level, algorithm-level, and hybrid-level. …”

Gene subset selection for lung cancer classification using a multi-objective strategy by Mohamad, Mohd. Saberi, Omatu, Sigeru, Deris, Safaai, Yoshioka, Michifuci

“…It obtains encouraging result on the data set as compared with an approach that uses single-objective strategy in genetic algorithms.…”
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Pathological infant cry analysis using wavelet packet transform and probabilistic neural network by Muthusamy, Hariharan, Sazali, Yaacob, Prof. Dr., Saidatul Ardeenaawatie, Awang

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Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals by Altaf, Hunain, Ibrahim, Siti Noorjannah, Mohd Azmin, Nor Fadhillah, Asnawi, Ani Liza, Walid, Balqis Hanisah, Harun, Noor Hasmiza

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Deep learning framework for hierarchical-based object identification and description by Alamro, Loai C. A.

“…The Deep learning (DL) and Computer Vision (CV) approaches allow computers to gain high-level understanding from images or videos. …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…In the third algorithm, a soft assignment technique using fuzzy encoding is used to transform low-level features into a higher-level feature representation. …”
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Classification algorithm for customer complaint using fuzzy approach by Razali, R., Jaafar, J.

“…The main challenge to extract the valuable information is a proper approach managing the complaint data, classification process and high level of uncertainties on the complaint and involvement of expertsâ�� opinion. …”
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Classification algorithm for customer complaint using fuzzy approach by Razali, R., Jaafar, J.

“…The main challenge to extract the valuable information is a proper approach managing the complaint data, classification process and high level of uncertainties on the complaint and involvement of expertsâ�� opinion. …”
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Classification model for chlorophyll content using CNN and aerial images by Wagimin, Mohd Nazuan, Ismail, Mohammad Hafiz, Mohd Fauzi, Shukor Sanim, Seng, Chuah Tse, Abd Latif, Zulkiflee, Muharam, Farrah Melissa, Mohd Zaki, Nurul Ain

“…The classification approach requires a discrete group for dependent variables instead of continuous numbers. …”
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Classification Of Cervical Cancer Stage From Pap Smear Tests by Sendal, Ken Irok

“…The performance of the proposed classification algorithm gave satisfactory results of accuracy, 91.9% for KNN classification and 95.0% for SVM classification.…”
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