Search Results - (( model validation between algorithm ) OR ( level classification based algorithm ))

TB-FusionNet: a multi-scale feature fusion algorithm with spatial and channel cross-attention for tuberculosis detection by Ding, Zeyu, Yaakob, Razali, Tieng Wei, Koh, Azman, Azreen, Mohd Rum, Siti Nurulain, Zakaria, Nor Fadhlina, Ahmad Nazri, Azree Shahril

“…Next, the algorithm computes the dependencies between feature channels at different levels, allowing low-level channel features to be appropriately enhanced or suppressed under the guidance of high-level channels, effectively improving the semantic consistency between cross-level features. …”
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Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network by Al-Hiyali, M.I., Yahya, N., Faye, I., Hussein, A.F.

“…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network by Al-Hiyali, M.I., Yahya, N., Faye, I., Hussein, A.F.

“…The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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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. …”
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Local threshold identification and gray level classification of butt joint welding imperfections using robot vision system by Mohd Shah, Hairol Nizam

“…The proposed approaches were validated through experiments with a KUKA welding robot in a realistic workshop environment. …”
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Implementation of Hybrid Indexing, Clustering and Classification Methods to Enhance Rural Development Programme in South Sulawesi by Muhammad, Faisal

“…The classification technique using the CSLI-Cluster, DVI, and HDI criteria showed that as many as 22 villages had the status of Less Development level, and 8 villages were declared Developed. …”
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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 results of the experiments show that the MCML classification algorithm successfully performs detailed classification and produces promising results for each classification level. …”
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Real-time oil palm fruit bunch ripeness grading system using image processing techniques by Alfatni, Meftah Salem M.

“…These results are optimal based on the thorns model. A new approach was developed using expert rules-based system. …”
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Symmetric Key Size for Different Level of Information Classification by Ibrahim, Subariah, Maarof, Mohd. Aizaini

“…Confidential information can be categorized into various levels of classification. The classification depends on the level of damage to an organization or to national security when the information is disclosed. …”
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Relationship between deforestation and land surface temperature across an elevation gradient using satellite imagery in Cameron Highlands, Malaysia by How, Darren Jin Aik

“…First, land cover classes and detection were identified using an Object-based Image Analysis (OBIA) classification technique on both Landsat 7 and 8 sensors, using a combination of nearest neighbour and multiresolution segmentation algorithm (MSA). …”
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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

“…This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.…”
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Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study by Sim, Doreen Ying Ying, Teh, Chee Siong, Ahmad Izuanuddin, Ismail

“…Prediction and/or classification accuracies of cfsw-SVM algorithms are significantly improved.…”
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Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

“…These features have been exploited in different algorithms for automatic classification of medical X-ray images. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

“…Overall, the proposed fuzzy rule-based diabetes diagnosis and level of care fuzzy model works well with most of the machine learning algorithms tested. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Additionally, the traffic are relying on the markers and scheduling algorithms to the service classes at the routers. The higher level priority agreements give a higher or equal probability than the lower level, this technique is perfect at a core router by scheduling algorithm. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

“…For this purpose, the dataset was randomly split into three sets, 60.0% for model training, 20.0% for model validating, and 20.0% for model testing. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

“…Deep Belief Network (DBN) is a sophisticated learning system that requires a high level of approach and executes well. The major contribution of this research is to introduce a Taylor-Bird Swarm optimization-based Deep Belief Network (Taylor-BSA-based DBN) for medical data classification. …”
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