Search Results - moderation classifications techniques

Comparison of measured maxillo-pharyngeal angle on lateral cervical radiograph & modified mallampati classification in predicting difficult laryngoscopy by Ming, Fung Eng

“…Available techniques have poor to moderate sensitivity and reliability for the task. …”
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An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab by Bassam Ali Qasem, Al-Qatab

“…Our proposed method introduces the intra-severity classification and adaptation techniques which are applied sequentially in two stages of system development. …”
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Per-pixel and sub-pixel classifications of high-resolution satellite data for mangrove species mapping by Kanniah, Kasturi Devi, Ng, Su Wai, Lau, Alvin Meng Shin, Rasib, Abd. Wahid

“…Conventional per-pixel classification techniques could not improve the classification accuracy when such high-resolution images are applied. …”
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Determination and classification of human stress index using nonparametric analysis of EEG signals / Norizam Sulaiman by Sulaiman, Norizam

“…The assignment of the stress index is verified by applying Z-score technique to the selected EEG features. The experiments established a 3-level index (Index 1, Index 2 and Index 3) which represents the stress levels of low stress, moderate stress and high stress at overall classification accuracy of 88.89%, classification sensitivity of 86.67 % and classification specificity of 100%. …”
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Determination and classification of human stress index using non parametric analysis of EEG signals / Norizam Sulaiman by Sulaiman, Norizam

“…The assignment of the stress index is verified by applying Z-score technique to the selected EEG features. The experiments established a 3-level index (Index 1, Index 2 and Index 3) which represents the stress levels of low stress, moderate stress and high stress at overall classification accuracy of 88.89%, classification sensitivity of 86.67 % and classification specificity of 100%. …”
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A telemedicine software application for asthma severity levels identification using wheeze sounds classification by Nabi, Fizza Ghulam, Shafiq, Muhammad, Sundaraj, Kenneth, Iqbal, Muhammad Shahid, Palaniappan, Rajkumar

“…MFCC-based features classification provides maximum accuracy of 99%, 90%, and 89% for mild, moderate, and severe samples, respectively. …”
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Transfer learning and hybrid deep convolutional neural networks models for autism spectrum disorder classification from EEG signals by Al-Qazzaz, Noor Kamal, Aldoori, Alaa A., Buniya, Ali K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom

“…Accordingly, the primary goal of this study is to use the pre-trained CNNs as classifiers in order to reap the benefits of transfer learning, and the secondary goal is to propose a hybrid model by employing decision tree (DT), K nearest neighbour (KNN), and a Support Vector Machine (SVM) machine learning classification techniques to categorise the features of the pre-trained CNN networks into mild, moderate, severe, and normal categories. …”
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Determination and classification of human stress index using non-parametric analysis of EEG signals by Norizam, Sulaiman

“…The assignment of the stress index is verified by applying Z-score technique to the selected EEG features. The experiments established a 3-level index (Index 1, Index 2 and Index 3) which represents the stress levels of low stress, moderate stress and high stress at overall classification accuracy of 88.89%, classification sensitivity of 86.67 % and classification specificity of 100%. …”
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NDVI Differencing and Post-classification to Detect Vegetation Changes in Halabja City, Iraq. by Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi, Al-doski, Jwan

“…The Normalized Difference Vegetation Index (NDVI) image differencing and post–classification techniques were applied. The NDVI was derived first then classified to produce vegetation maps followed by quantifying the changes.The results indicated a drastic decrease in the dense, sparse and moderate vegetation by55%, 7% and 9% respectively. …”
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Sentiment classification of customer reviews based on fuzzy logic by Nadali, Samaneh, Azmi Murad, Masrah Azrifah, Abdul Kadir, Rabiah

“…Most existing method utilize a list of opinion words for sentiment classification. whereas, this paper propose a fuzzy logic model to perform semantic classifications of customers review into the following sub-classes: very weak, weak, moderate, very strong and strong by combinations adjective, adverb and verb to increase holistic the accuracy of lexicon approach. …”
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Evaluation Of Texture Feature Based On Basic Local Binary Pattern For Wood Defect Classification by Ibrahim, Eihab Abdelkariem Bashir, Hashim, Ummi Rabaah, Salahuddin, Lizawati, Ismail, Nor Haslinda, Ngo, Hea Choon, Kanchymalay, Kasturi, Zabri @ Suhaimi, Siti Normi

“…It indicates that the proposed technique works moderately well to classify wood defects. …”
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Pedological Study and Classification of Some Soils Developed on Volcanic Rocks in Jerantut District, Pahang by Saleh, Ibrahim

“…The soils were characterized by physical, chemical, mineralogical and micromorphological techniques. Classification of the soils were carried out according to Soil Taxonomy (USDA, 1996), FAO/UNESCO Legend (1990) and Malaysian Classification Systems (1992). …”
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Restoration of hazy satellite data based on spectral and statistical methods by Saiful Bahari, Nurul Iman, Ahmad, Asmala, Mohd Aboobaider, Burhanuddin, Sakidin, Hamzah, Razali, Muhammad Fahmi, Mohamad Isa, Mohd Saari

“…It is revealed that, the technique is able to improve the classification accuracy to the acceptable levels for data with moderate visibilities. …”
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Restoration of hazy data based on spectral and statistical methods by Saiful Bahari, N.i., Ahmad, A., Aboobaider, B.M., Razali, M.F., Sakidin, H., Mohamad Isa, M.S.

“…It is revealed that, the technique is able to improve the classification accuracy to the acceptable levels for data with moderate visibilities. …”
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Restoration of hazy data based on spectral and statistical methods by Saiful Bahari, N.i., Ahmad, A., Aboobaider, B.M., Razali, M.F., Sakidin, H., Mohamad Isa, M.S.

“…It is revealed that, the technique is able to improve the classification accuracy to the acceptable levels for data with moderate visibilities. …”
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Restoration of hazy data based on spectral and statistical methods by Saiful Bahari, N.i., Ahmad, A., Aboobaider, B.M., Razali, M.F., Sakidin, H., Mohamad Isa, M.S.

“…It is revealed that, the technique is able to improve the classification accuracy to the acceptable levels for data with moderate visibilities. …”
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Capability of integrated MODIS imagery and ALOS for oil palm, rubber and forest areas mapping in tropical forest regions by Mohd Razali, Sheriza, Marin, Arnaldo, Nuruddin, Ahmad Ainuddin, Mohd Shafri, Helmi Zulhaidi, Abdul Hamid, Hazandy

“…This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. …”
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Correlation of radiographic and echocardiographic findings with clinical outcome in canine heart patients by Lee, Chin Choo, Goh, Yong Meng

“…Kappa’s test of agreement showed moderate degree of agreement between severity classification based on radiographic and echocardiographic findings with a kappa value of 0.60 (p=0.003). …”
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Complexity approximation of classification task for large dataset ensemble artificial neural networks by Mumtazimah, Mohamad, Saman, M.Y.M, Hamid, N.A.

“…The main idea behind this, is lie on large dataset classification complexity and burden are to be moderated by using partitioning for parallel tasks and combining them to enhance the capability of a classifier. …”
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Complexity Approximation of Classification Task for Large Dataset Ensemble Artificial Neural Networks by Mohamad, Prof. Madya Ts. Dr. Mumtazimah, Abd Hamid, Nazirah

“…The main idea behind this, is lie on large dataset classification complexity and burden are to be moderated by using partitioning for parallel tasks and combining them to enhance the capability of a classifier. …”
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